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blog/Statistics_10days-day0.html
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@ -155,8 +155,8 @@ For a continuous probability distribution, the median is the value such that a n
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Sample : [64630, 11735, 14216, 99233, 14470, 4978, 73429, 38120, 51135, 67060, 4978, 73429] <div class="highlight"><pre><span></span><span class="n">Sample</span> <span class="p">:</span> <span class="p">[</span><span class="mi">64630</span><span class="p">,</span> <span class="mi">11735</span><span class="p">,</span> <span class="mi">14216</span><span class="p">,</span> <span class="mi">99233</span><span class="p">,</span> <span class="mi">14470</span><span class="p">,</span> <span class="mi">4978</span><span class="p">,</span> <span class="mi">73429</span><span class="p">,</span> <span class="mi">38120</span><span class="p">,</span> <span class="mi">51135</span><span class="p">,</span> <span class="mi">67060</span><span class="p">,</span> <span class="mi">4978</span><span class="p">,</span> <span class="mi">73429</span><span class="p">]</span>
Mean : 43117.75, Median : 44627.5, Mode : 4978 <span class="n">Mean</span> <span class="p">:</span> <span class="mi">43117</span><span class="p">.</span><span class="mi">75</span><span class="p">,</span> <span class="n">Median</span> <span class="p">:</span> <span class="mi">44627</span><span class="p">.</span><span class="mi">5</span><span class="p">,</span> <span class="k">Mode</span> <span class="p">:</span> <span class="mi">4978</span>
</pre></div> </pre></div>
@ -169,7 +169,7 @@ Mean : 43117.75, Median : 44627.5, Mode : 4978
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>32.0 <div class="highlight"><pre><span></span><span class="mi">32</span><span class="p">.</span><span class="mi">0</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -185,7 +185,7 @@ Mean : 43117.75, Median : 44627.5, Mode : 4978
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

10
blog/Statistics_10days-day1.html
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@ -165,8 +165,8 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Sample : [3, 7, 8, 5, 12, 14, 21, 13, 18] <div class="highlight"><pre><span></span><span class="n">Sample</span> <span class="p">:</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">14</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">18</span><span class="p">]</span>
Q1 : 6.0, Q2 : 12, Q3 : 16.0 <span class="n">Q1</span> <span class="p">:</span> <span class="mi">6</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="n">Q2</span> <span class="p">:</span> <span class="mi">12</span><span class="p">,</span> <span class="n">Q3</span> <span class="p">:</span> <span class="mi">16</span><span class="p">.</span><span class="mi">0</span>
</pre></div> </pre></div>
@ -178,7 +178,7 @@ Q1 : 6.0, Q2 : 12, Q3 : 16.0
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Interquatile range : 10.0 <div class="highlight"><pre><span></span><span class="n">Interquatile</span> <span class="n">range</span> <span class="p">:</span> <span class="mi">10</span><span class="p">.</span><span class="mi">0</span>
</pre></div> </pre></div>
@ -203,7 +203,7 @@ Q1 : 6.0, Q2 : 12, Q3 : 16.0
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>The distribution [400.0, 100.0, 0.0, 400.0, 100.0] has a standard deviation of 14.142135623730951 <div class="highlight"><pre><span></span><span class="n">The</span> <span class="n">distribution</span> <span class="p">[</span><span class="mi">400</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="mi">100</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="mi">400</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="mi">100</span><span class="p">.</span><span class="mi">0</span><span class="p">]</span> <span class="n">has</span> <span class="n">a</span> <span class="n">standard</span> <span class="n">deviation</span> <span class="k">of</span> <span class="mi">14</span><span class="p">.</span><span class="mi">142135623730951</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -219,7 +219,7 @@ Q1 : 6.0, Q2 : 12, Q3 : 16.0
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

8
blog/Statistics_10days-day2.html
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@ -233,7 +233,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0.8333333333333334 <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">.</span><span class="mi">8333333333333334</span>
</pre></div> </pre></div>
@ -262,7 +262,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0.1111111111111111 <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">.</span><span class="mi">1111111111111111</span>
</pre></div> </pre></div>
@ -357,7 +357,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0.40476190476190477 <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">.</span><span class="mi">40476190476190477</span>
</pre></div> </pre></div>
@ -429,7 +429,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
blog/Statistics_10days-day3.html
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@ -256,7 +256,7 @@ we call B the event "a blue ball is drawn" and R the event "a red ball is drawn"
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

14
blog/Statistics_10days-day4.html
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@ -144,7 +144,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>The probability of having a boy is p=0.521531 <div class="highlight"><pre><span></span><span class="n">The</span> <span class="n">probability</span> <span class="k">of</span> <span class="k">having</span> <span class="n">a</span> <span class="n">boy</span> <span class="k">is</span> <span class="n">p</span><span class="o">=</span><span class="mi">0</span><span class="p">.</span><span class="mi">521531</span>
</pre></div> </pre></div>
@ -167,7 +167,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>probability of getting at least 3 boys in a family with exactly 6 children : 0.696 <div class="highlight"><pre><span></span><span class="n">probability</span> <span class="k">of</span> <span class="n">getting</span> <span class="k">at</span> <span class="n">least</span> <span class="mi">3</span> <span class="n">boys</span> <span class="k">in</span> <span class="n">a</span> <span class="n">family</span> <span class="k">with</span> <span class="n">exactly</span> <span class="mi">6</span> <span class="n">children</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">696</span>
</pre></div> </pre></div>
@ -188,7 +188,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>The probability of getting less than 2 faulty pistons in a batch is : 0.891 <div class="highlight"><pre><span></span><span class="n">The</span> <span class="n">probability</span> <span class="k">of</span> <span class="n">getting</span> <span class="k">less</span> <span class="k">than</span> <span class="mi">2</span> <span class="n">faulty</span> <span class="n">pistons</span> <span class="k">in</span> <span class="n">a</span> <span class="n">batch</span> <span class="k">is</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">891</span>
</pre></div> </pre></div>
@ -203,7 +203,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>The probability of getting at least 2 faulty pistons in a batch is : 0.342 <div class="highlight"><pre><span></span><span class="n">The</span> <span class="n">probability</span> <span class="k">of</span> <span class="n">getting</span> <span class="k">at</span> <span class="n">least</span> <span class="mi">2</span> <span class="n">faulty</span> <span class="n">pistons</span> <span class="k">in</span> <span class="n">a</span> <span class="n">batch</span> <span class="k">is</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">342</span>
</pre></div> </pre></div>
@ -219,7 +219,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>The probability that the first defect is found during the fith inspection is 0.038 <div class="highlight"><pre><span></span><span class="n">The</span> <span class="n">probability</span> <span class="n">that</span> <span class="n">the</span> <span class="k">first</span> <span class="n">defect</span> <span class="k">is</span> <span class="k">found</span> <span class="n">during</span> <span class="n">the</span> <span class="n">fith</span> <span class="n">inspection</span> <span class="k">is</span> <span class="mi">0</span><span class="p">.</span><span class="mi">038</span>
</pre></div> </pre></div>
@ -239,7 +239,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>The probability that the first defect is found during the first 5 inspection is 0.868 <div class="highlight"><pre><span></span><span class="n">The</span> <span class="n">probability</span> <span class="n">that</span> <span class="n">the</span> <span class="k">first</span> <span class="n">defect</span> <span class="k">is</span> <span class="k">found</span> <span class="n">during</span> <span class="n">the</span> <span class="k">first</span> <span class="mi">5</span> <span class="n">inspection</span> <span class="k">is</span> <span class="mi">0</span><span class="p">.</span><span class="mi">868</span>
</pre></div> </pre></div>
@ -311,7 +311,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

18
blog/Statistics_10days-day5.html
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@ -147,7 +147,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that a random variable X following a Poisson distribution of mean 2.5 equals 5 : 0.067 <div class="highlight"><pre><span></span><span class="nv">Probability</span> <span class="nv">that</span> <span class="nv">a</span> <span class="k">random</span> <span class="nv">variable</span> <span class="nv">X</span> <span class="nv">following</span> <span class="nv">a</span> <span class="nv">Poisson</span> <span class="nv">distribution</span> <span class="nv">of</span> <span class="nv">mean</span> <span class="mi">2</span>.<span class="mi">5</span> <span class="nv">equals</span> <span class="mi">5</span> : <span class="mi">0</span>.<span class="mi">067</span>
</pre></div> </pre></div>
@ -179,8 +179,8 @@ Since the expectation is a linear operator :
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Expected cost to run machine A : 226.176 <div class="highlight"><pre><span></span><span class="n">Expected</span> <span class="n">cost</span> <span class="k">to</span> <span class="n">run</span> <span class="n">machine</span> <span class="n">A</span> <span class="p">:</span> <span class="mi">226</span><span class="p">.</span><span class="mi">176</span>
Expected cost to run machine A : 286.1 <span class="n">Expected</span> <span class="n">cost</span> <span class="k">to</span> <span class="n">run</span> <span class="n">machine</span> <span class="n">A</span> <span class="p">:</span> <span class="mi">286</span><span class="p">.</span><span class="mi">1</span>
</pre></div> </pre></div>
@ -206,7 +206,7 @@ Between 20 and 22 hours?</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that the car is built in less than 19.5 hours : 0.401 <div class="highlight"><pre><span></span><span class="n">Probability</span> <span class="n">that</span> <span class="n">the</span> <span class="n">car</span> <span class="k">is</span> <span class="n">built</span> <span class="k">in</span> <span class="k">less</span> <span class="k">than</span> <span class="mi">19</span><span class="p">.</span><span class="mi">5</span> <span class="n">hours</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">401</span>
</pre></div> </pre></div>
@ -216,7 +216,7 @@ Between 20 and 22 hours?</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that the car is built between 20 and 22 hours : 0.341 <div class="highlight"><pre><span></span><span class="n">Probability</span> <span class="n">that</span> <span class="n">the</span> <span class="n">car</span> <span class="k">is</span> <span class="n">built</span> <span class="k">between</span> <span class="mi">20</span> <span class="k">and</span> <span class="mi">22</span> <span class="n">hours</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">341</span>
</pre></div> </pre></div>
@ -237,7 +237,7 @@ Between 20 and 22 hours?</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that the the student scored higher than 80 : 0.159 <div class="highlight"><pre><span></span><span class="n">Probability</span> <span class="n">that</span> <span class="n">the</span> <span class="n">the</span> <span class="n">student</span> <span class="n">scored</span> <span class="n">higher</span> <span class="k">than</span> <span class="mi">80</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">159</span>
</pre></div> </pre></div>
@ -249,7 +249,7 @@ Between 20 and 22 hours?</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that the the student passed the test : 0.841 <div class="highlight"><pre><span></span><span class="n">Probability</span> <span class="n">that</span> <span class="n">the</span> <span class="n">the</span> <span class="n">student</span> <span class="n">passed</span> <span class="n">the</span> <span class="n">test</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">841</span>
</pre></div> </pre></div>
@ -259,7 +259,7 @@ Between 20 and 22 hours?</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that the student failed the test: 0.159 <div class="highlight"><pre><span></span><span class="n">Probability</span> <span class="n">that</span> <span class="n">the</span> <span class="n">student</span> <span class="n">failed</span> <span class="n">the</span> <span class="n">test</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">159</span>
</pre></div> </pre></div>
@ -331,7 +331,7 @@ Between 20 and 22 hours?</p>
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

10
blog/Statistics_10days-day6.html
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@ -152,7 +152,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that all the boxes can be lifted by the elevator : 0.009815328628645315 <div class="highlight"><pre><span></span><span class="n">Probability</span> <span class="n">that</span> <span class="k">all</span> <span class="n">the</span> <span class="n">boxes</span> <span class="n">can</span> <span class="n">be</span> <span class="n">lifted</span> <span class="k">by</span> <span class="n">the</span> <span class="n">elevator</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">009815328628645315</span>
</pre></div> </pre></div>
@ -175,7 +175,7 @@ The total number of tickets bought follows a normal distribution of mean <span c
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Probability that all the students can purchase tickets : 0.691462461274013 <div class="highlight"><pre><span></span><span class="n">Probability</span> <span class="n">that</span> <span class="k">all</span> <span class="n">the</span> <span class="n">students</span> <span class="n">can</span> <span class="n">purchase</span> <span class="n">tickets</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">691462461274013</span>
</pre></div> </pre></div>
@ -197,8 +197,8 @@ The total number of tickets bought follows a normal distribution of mean <span c
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>A = 484.32 <div class="highlight"><pre><span></span><span class="n">A</span> <span class="o">=</span> <span class="mi">484</span><span class="p">.</span><span class="mi">32</span>
B = 515.68 <span class="n">B</span> <span class="o">=</span> <span class="mi">515</span><span class="p">.</span><span class="mi">68</span>
</pre></div> </pre></div>
@ -270,7 +270,7 @@ B = 515.68
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

8
blog/Statistics_10days-day7.html
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@ -155,7 +155,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0.6124721937208479 <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">.</span><span class="mi">6124721937208479</span>
</pre></div> </pre></div>
@ -174,7 +174,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0.6124721937208479 <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">.</span><span class="mi">6124721937208479</span>
</pre></div> </pre></div>
@ -200,7 +200,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0.9030303030303031 <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">.</span><span class="mi">9030303030303031</span>
</pre></div> </pre></div>
@ -272,7 +272,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

4
blog/Statistics_10days-day8.html
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@ -161,7 +161,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>If a student scored 80 on the math test, he would most likely score a 78.288 in statistics <div class="highlight"><pre><span></span><span class="k">If</span> <span class="nv">a</span> <span class="nv">student</span> <span class="nv">scored</span> <span class="mi">80</span> <span class="nv">on</span> <span class="nv">the</span> <span class="nv">math</span> <span class="nv">test</span>, <span class="nv">he</span> <span class="nv">would</span> <span class="nv">most</span> <span class="nv">likely</span> <span class="nv">score</span> <span class="nv">a</span> <span class="mi">78</span>.<span class="mi">288</span> <span class="nv">in</span> <span class="nv">statistics</span>
</pre></div> </pre></div>
@ -277,7 +277,7 @@ $$</div>
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

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blog/Statistics_10days-day9.html
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@ -178,7 +178,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>array([105.21455835, 142.67095131, 132.93605469, 129.70175405]) <div class="highlight"><pre><span></span><span class="nb">array</span><span class="p">([</span><span class="mi">105</span><span class="p">.</span><span class="mi">21455835</span><span class="p">,</span> <span class="mi">142</span><span class="p">.</span><span class="mi">67095131</span><span class="p">,</span> <span class="mi">132</span><span class="p">.</span><span class="mi">93605469</span><span class="p">,</span> <span class="mi">129</span><span class="p">.</span><span class="mi">70175405</span><span class="p">])</span>
</pre></div> </pre></div>
@ -203,7 +203,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>array([105.21455835, 142.67095131, 132.93605469, 129.70175405]) <div class="highlight"><pre><span></span><span class="nb">array</span><span class="p">([</span><span class="mi">105</span><span class="p">.</span><span class="mi">21455835</span><span class="p">,</span> <span class="mi">142</span><span class="p">.</span><span class="mi">67095131</span><span class="p">,</span> <span class="mi">132</span><span class="p">.</span><span class="mi">93605469</span><span class="p">,</span> <span class="mi">129</span><span class="p">.</span><span class="mi">70175405</span><span class="p">])</span>
</pre></div> </pre></div>
@ -275,7 +275,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

8
cryptocurrencies/mayer_multiple.html
View File

@ -323,8 +323,8 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Mayer multiple 0.5108290958630005 <div class="highlight"><pre><span></span><span class="n">Mayer</span> <span class="n">multiple</span> <span class="mi">0</span><span class="p">.</span><span class="mi">5108290958630005</span>
Mayer multiple average 1.3789102045356179 <span class="n">Mayer</span> <span class="n">multiple</span> <span class="n">average</span> <span class="mi">1</span><span class="p">.</span><span class="mi">3789102045356179</span>
</pre></div> </pre></div>
@ -346,7 +346,7 @@ Mayer multiple average 1.3789102045356179
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[] <div class="highlight"><pre><span></span><span class="p">[]</span>
</pre></div> </pre></div>
@ -365,7 +365,7 @@ Mayer multiple average 1.3789102045356179
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

24
dl/csv_logger_keras.html
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@ -177,22 +177,22 @@ Let's first import some libraries</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Epoch 1/5 <div class="highlight"><pre><span></span><span class="n">Epoch</span> <span class="mi">1</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 9s 148us/step - loss: 0.5020 - acc: 0.8234 - mean_absolute_error: 4.4200 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">9</span><span class="n">s</span> <span class="mi">148</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">5020</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8234</span> <span class="o">-</span> <span class="n">mean_absolute_error</span><span class="p">:</span> <span class="mi">4</span><span class="p">.</span><span class="mi">4200</span>
Epoch 2/5 <span class="n">Epoch</span> <span class="mi">2</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 8s 138us/step - loss: 0.3765 - acc: 0.8630 - mean_absolute_error: 4.4200 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">8</span><span class="n">s</span> <span class="mi">138</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3765</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8630</span> <span class="o">-</span> <span class="n">mean_absolute_error</span><span class="p">:</span> <span class="mi">4</span><span class="p">.</span><span class="mi">4200</span>
Epoch 3/5 <span class="n">Epoch</span> <span class="mi">3</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 8s 129us/step - loss: 0.3371 - acc: 0.8789 - mean_absolute_error: 4.4200 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">8</span><span class="n">s</span> <span class="mi">129</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3371</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8789</span> <span class="o">-</span> <span class="n">mean_absolute_error</span><span class="p">:</span> <span class="mi">4</span><span class="p">.</span><span class="mi">4200</span>
Epoch 4/5 <span class="n">Epoch</span> <span class="mi">4</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 8s 133us/step - loss: 0.3129 - acc: 0.8843 - mean_absolute_error: 4.4200 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">8</span><span class="n">s</span> <span class="mi">133</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3129</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8843</span> <span class="o">-</span> <span class="n">mean_absolute_error</span><span class="p">:</span> <span class="mi">4</span><span class="p">.</span><span class="mi">4200</span>
Epoch 5/5 <span class="n">Epoch</span> <span class="mi">5</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 9s 151us/step - loss: 0.2952 - acc: 0.8916 - mean_absolute_error: 4.4200 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">9</span><span class="n">s</span> <span class="mi">151</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">2952</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8916</span> <span class="o">-</span> <span class="n">mean_absolute_error</span><span class="p">:</span> <span class="mi">4</span><span class="p">.</span><span class="mi">4200</span>
&lt;keras.callbacks.History at 0x1582adc6780&gt; <span class="o">&lt;</span><span class="n">keras</span><span class="p">.</span><span class="n">callbacks</span><span class="p">.</span><span class="n">History</span> <span class="k">at</span> <span class="mi">0</span><span class="n">x1582adc6780</span><span class="o">&gt;</span>
</pre></div> </pre></div>
@ -279,7 +279,7 @@ Epoch 5/5
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

28
dl/keras_info.html
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@ -133,19 +133,19 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>_________________________________________________________________ <div class="highlight"><pre><span></span><span class="n">_________________________________________________________________</span>
Layer (type) Output Shape Param # <span class="n">Layer</span> <span class="p">(</span><span class="k">type</span><span class="p">)</span> <span class="k">Output</span> <span class="n">Shape</span> <span class="n">Param</span> <span class="o">#</span>
================================================================= <span class="o">=================================================================</span>
flatten_2 (Flatten) (None, 784) 0 <span class="n">flatten_2</span> <span class="p">(</span><span class="n">Flatten</span><span class="p">)</span> <span class="p">(</span><span class="k">None</span><span class="p">,</span> <span class="mi">784</span><span class="p">)</span> <span class="mi">0</span>
_________________________________________________________________ <span class="n">_________________________________________________________________</span>
dense_3 (Dense) (None, 128) 100480 <span class="n">dense_3</span> <span class="p">(</span><span class="n">Dense</span><span class="p">)</span> <span class="p">(</span><span class="k">None</span><span class="p">,</span> <span class="mi">128</span><span class="p">)</span> <span class="mi">100480</span>
_________________________________________________________________ <span class="n">_________________________________________________________________</span>
dense_4 (Dense) (None, 10) 1290 <span class="n">dense_4</span> <span class="p">(</span><span class="n">Dense</span><span class="p">)</span> <span class="p">(</span><span class="k">None</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> <span class="mi">1290</span>
================================================================= <span class="o">=================================================================</span>
Total params: 101,770 <span class="n">Total</span> <span class="n">params</span><span class="p">:</span> <span class="mi">101</span><span class="p">,</span><span class="mi">770</span>
Trainable params: 101,770 <span class="n">Trainable</span> <span class="n">params</span><span class="p">:</span> <span class="mi">101</span><span class="p">,</span><span class="mi">770</span>
Non-trainable params: 0 <span class="n">Non</span><span class="o">-</span><span class="n">trainable</span> <span class="n">params</span><span class="p">:</span> <span class="mi">0</span>
_________________________________________________________________ <span class="n">_________________________________________________________________</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -161,7 +161,7 @@ _________________________________________________________________
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

4
dl/keras_input.html
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@ -133,7 +133,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>(None, 28, 28) <div class="highlight"><pre><span></span><span class="p">(</span><span class="k">None</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">28</span><span class="p">)</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -149,7 +149,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

8
dl/keras_install.html
View File

@ -126,17 +126,17 @@
</header> </header>
<div class='article_content'> <div class='article_content'>
<p>Keras with the Tensorflow backend can be installed by running the following conda command </p> <p>Keras with the Tensorflow backend can be installed by running the following conda command </p>
<div class="highlight"><pre><span></span>conda install -c conda-forge keras tensorflow <div class="highlight"><pre><span></span><span class="n">conda</span> <span class="n">install</span> <span class="o">-</span><span class="k">c</span> <span class="n">conda</span><span class="o">-</span><span class="n">forge</span> <span class="n">keras</span> <span class="n">tensorflow</span>
</pre></div> </pre></div>
<p>If you want a Intel CPU optimized version, install tensorflow-mkl</p> <p>If you want a Intel CPU optimized version, install tensorflow-mkl</p>
<div class="highlight"><pre><span></span>conda install -c conda-forge keras tensorflow-mkl <div class="highlight"><pre><span></span><span class="n">conda</span> <span class="n">install</span> <span class="o">-</span><span class="k">c</span> <span class="n">conda</span><span class="o">-</span><span class="n">forge</span> <span class="n">keras</span> <span class="n">tensorflow</span><span class="o">-</span><span class="n">mkl</span>
</pre></div> </pre></div>
<p>A GPU compatible version is also available </p> <p>A GPU compatible version is also available </p>
<div class="highlight"><pre><span></span>conda install -c conda-forge keras tensorflow-gpu <div class="highlight"><pre><span></span><span class="n">conda</span> <span class="n">install</span> <span class="o">-</span><span class="k">c</span> <span class="n">conda</span><span class="o">-</span><span class="n">forge</span> <span class="n">keras</span> <span class="n">tensorflow</span><span class="o">-</span><span class="n">gpu</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -152,7 +152,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

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dl/keras_load.html
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@ -138,7 +138,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>keras.engine.sequential.Sequential <div class="highlight"><pre><span></span><span class="n">keras</span><span class="p">.</span><span class="n">engine</span><span class="p">.</span><span class="n">sequential</span><span class="p">.</span><span class="n">Sequential</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -154,7 +154,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

26
dl/model_checkpoint_keras.html
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@ -192,22 +192,22 @@ Let's first import some libraries</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Epoch 1/5 <div class="highlight"><pre><span></span><span class="n">Epoch</span> <span class="mi">1</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 29s 478us/step - loss: 0.3975 - acc: 0.8575 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">29</span><span class="n">s</span> <span class="mi">478</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3975</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8575</span>
Epoch 2/5 <span class="n">Epoch</span> <span class="mi">2</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 98s 2ms/step - loss: 0.3498 - acc: 0.8721 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">98</span><span class="n">s</span> <span class="mi">2</span><span class="n">ms</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3498</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8721</span>
Epoch 3/5 <span class="n">Epoch</span> <span class="mi">3</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 95s 2ms/step - loss: 0.3213 - acc: 0.8825 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">95</span><span class="n">s</span> <span class="mi">2</span><span class="n">ms</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3213</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8825</span>
Epoch 4/5 <span class="n">Epoch</span> <span class="mi">4</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 64s 1ms/step - loss: 0.3021 - acc: 0.8887: 6s - loss: <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">64</span><span class="n">s</span> <span class="mi">1</span><span class="n">ms</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3021</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8887</span><span class="p">:</span> <span class="mi">6</span><span class="n">s</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span>
Epoch 5/5 <span class="n">Epoch</span> <span class="mi">5</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 61s 1ms/step - loss: 0.2855 - acc: 0.8953: 4s - loss: 0.284 - ETA: 3s - loss: - ETA: <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">61</span><span class="n">s</span> <span class="mi">1</span><span class="n">ms</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">2855</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8953</span><span class="p">:</span> <span class="mi">4</span><span class="n">s</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">284</span> <span class="o">-</span> <span class="n">ETA</span><span class="p">:</span> <span class="mi">3</span><span class="n">s</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="o">-</span> <span class="n">ETA</span><span class="p">:</span>
&lt;keras.callbacks.History at 0x1d70aa62f28&gt; <span class="o">&lt;</span><span class="n">keras</span><span class="p">.</span><span class="n">callbacks</span><span class="p">.</span><span class="n">History</span> <span class="k">at</span> <span class="mi">0</span><span class="n">x1d70aa62f28</span><span class="o">&gt;</span>
</pre></div> </pre></div>
@ -219,7 +219,7 @@ Epoch 5/5
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>The model is saved to my_model.h5 <div class="highlight"><pre><span></span><span class="n">The</span> <span class="n">model</span> <span class="k">is</span> <span class="n">saved</span> <span class="k">to</span> <span class="n">my_model</span><span class="p">.</span><span class="n">h5</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -235,7 +235,7 @@ Epoch 5/5
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

56
dl/tensorboard_keras.html
View File

@ -164,22 +164,22 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Epoch 1/5 <div class="highlight"><pre><span></span><span class="n">Epoch</span> <span class="mi">1</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 9s 143us/step - loss: 0.4939 - acc: 0.8254 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">9</span><span class="n">s</span> <span class="mi">143</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">4939</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8254</span>
Epoch 2/5 <span class="n">Epoch</span> <span class="mi">2</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 11s 182us/step - loss: 0.3688 - acc: 0.8661 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">11</span><span class="n">s</span> <span class="mi">182</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3688</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8661</span>
Epoch 3/5 <span class="n">Epoch</span> <span class="mi">3</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 10s 169us/step - loss: 0.3305 - acc: 0.8798 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">10</span><span class="n">s</span> <span class="mi">169</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3305</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8798</span>
Epoch 4/5 <span class="n">Epoch</span> <span class="mi">4</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 21s 350us/step - loss: 0.3079 - acc: 0.8874 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">21</span><span class="n">s</span> <span class="mi">350</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3079</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8874</span>
Epoch 5/5 <span class="n">Epoch</span> <span class="mi">5</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 18s 302us/step - loss: 0.2889 - acc: 0.8927 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">18</span><span class="n">s</span> <span class="mi">302</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">2889</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8927</span>
&lt;keras.callbacks.History at 0x235c1bc1be0&gt; <span class="o">&lt;</span><span class="n">keras</span><span class="p">.</span><span class="n">callbacks</span><span class="p">.</span><span class="n">History</span> <span class="k">at</span> <span class="mi">0</span><span class="n">x235c1bc1be0</span><span class="o">&gt;</span>
</pre></div> </pre></div>
@ -189,8 +189,8 @@ Epoch 5/5
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>10000/10000 [==============================] - 1s 67us/step <div class="highlight"><pre><span></span><span class="mi">10000</span><span class="o">/</span><span class="mi">10000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="n">s</span> <span class="mi">67</span><span class="n">us</span><span class="o">/</span><span class="n">step</span>
Test accuracy : 0.8763 <span class="n">Test</span> <span class="n">accuracy</span> <span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8763</span>
</pre></div> </pre></div>
@ -200,8 +200,8 @@ Test accuracy : 0.8763
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[1.8075149e-05 3.6810281e-08 6.3094416e-07 5.1111499e-07 1.6264809e-06 <div class="highlight"><pre><span></span><span class="p">[</span><span class="mi">1</span><span class="p">.</span><span class="mi">8075149</span><span class="n">e</span><span class="o">-</span><span class="mi">05</span> <span class="mi">3</span><span class="p">.</span><span class="mi">6810281</span><span class="n">e</span><span class="o">-</span><span class="mi">08</span> <span class="mi">6</span><span class="p">.</span><span class="mi">3094416</span><span class="n">e</span><span class="o">-</span><span class="mi">07</span> <span class="mi">5</span><span class="p">.</span><span class="mi">1111499</span><span class="n">e</span><span class="o">-</span><span class="mi">07</span> <span class="mi">1</span><span class="p">.</span><span class="mi">6264809</span><span class="n">e</span><span class="o">-</span><span class="mi">06</span>
3.5973577e-04 1.0840570e-06 3.1453002e-02 1.7062060e-06 9.6816361e-01] <span class="mi">3</span><span class="p">.</span><span class="mi">5973577</span><span class="n">e</span><span class="o">-</span><span class="mi">04</span> <span class="mi">1</span><span class="p">.</span><span class="mi">0840570</span><span class="n">e</span><span class="o">-</span><span class="mi">06</span> <span class="mi">3</span><span class="p">.</span><span class="mi">1453002</span><span class="n">e</span><span class="o">-</span><span class="mi">02</span> <span class="mi">1</span><span class="p">.</span><span class="mi">7062060</span><span class="n">e</span><span class="o">-</span><span class="mi">06</span> <span class="mi">9</span><span class="p">.</span><span class="mi">6816361</span><span class="n">e</span><span class="o">-</span><span class="mi">01</span><span class="p">]</span>
</pre></div> </pre></div>
@ -235,7 +235,7 @@ Test accuracy : 0.8763
<p>TensorBoard will return a http address </p> <p>TensorBoard will return a http address </p>
<div class="highlight"><pre><span></span>TensorBoard 1.12.0 at http://localhost:6006 (Press CTRL+C to quit) <div class="highlight"><pre><span></span><span class="n">TensorBoard</span> <span class="mi">1</span><span class="p">.</span><span class="mi">12</span><span class="p">.</span><span class="mi">0</span> <span class="k">at</span> <span class="n">http</span><span class="p">:</span><span class="o">//</span><span class="n">localhost</span><span class="p">:</span><span class="mi">6006</span> <span class="p">(</span><span class="n">Press</span> <span class="n">CTRL</span><span class="o">+</span><span class="k">C</span> <span class="k">to</span> <span class="n">quit</span><span class="p">)</span>
</pre></div> </pre></div>
@ -244,22 +244,22 @@ Test accuracy : 0.8763
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Epoch 1/5 <div class="highlight"><pre><span></span><span class="n">Epoch</span> <span class="mi">1</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 41s 684us/step - loss: 0.4990 - acc: 0.8241 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">41</span><span class="n">s</span> <span class="mi">684</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">4990</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8241</span>
Epoch 2/5 <span class="n">Epoch</span> <span class="mi">2</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 49s 812us/step - loss: 0.3765 - acc: 0.8648 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">49</span><span class="n">s</span> <span class="mi">812</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3765</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8648</span>
Epoch 3/5 <span class="n">Epoch</span> <span class="mi">3</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 46s 765us/step - loss: 0.3392 - acc: 0.8766 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">46</span><span class="n">s</span> <span class="mi">765</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3392</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8766</span>
Epoch 4/5 <span class="n">Epoch</span> <span class="mi">4</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 48s 794us/step - loss: 0.3135 - acc: 0.8836 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">48</span><span class="n">s</span> <span class="mi">794</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">3135</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8836</span>
Epoch 5/5 <span class="n">Epoch</span> <span class="mi">5</span><span class="o">/</span><span class="mi">5</span>
60000/60000 [==============================] - 49s 813us/step - loss: 0.2971 - acc: 0.8897 <span class="mi">60000</span><span class="o">/</span><span class="mi">60000</span> <span class="p">[</span><span class="o">==============================</span><span class="p">]</span> <span class="o">-</span> <span class="mi">49</span><span class="n">s</span> <span class="mi">813</span><span class="n">us</span><span class="o">/</span><span class="n">step</span> <span class="o">-</span> <span class="n">loss</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">2971</span> <span class="o">-</span> <span class="n">acc</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8897</span>
&lt;keras.callbacks.History at 0x235be1c76d8&gt; <span class="o">&lt;</span><span class="n">keras</span><span class="p">.</span><span class="n">callbacks</span><span class="p">.</span><span class="n">History</span> <span class="k">at</span> <span class="mi">0</span><span class="n">x235be1c76d8</span><span class="o">&gt;</span>
</pre></div> </pre></div>
@ -280,7 +280,7 @@ Epoch 5/5
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

10
index.html
View File

@ -382,7 +382,7 @@
</div> </div>
<div class="panel-body"> <div class="panel-body">
<ul> <ul>
<li><a href="./python/case_config.html">Case sensitive ConfigParser</a></li> <li><a href="./python/iterate_dict.html">Iterate over a dictionnary</a></li>
<li><a href="./python/write_config_file.html">Write a value to a config file</a></li> <li><a href="./python/write_config_file.html">Write a value to a config file</a></li>
<li><a href="./python/config_parse.html">Parse variable from config file</a></li> <li><a href="./python/config_parse.html">Parse variable from config file</a></li>
<li><a href="./python/randint.html">Random integer</a></li> <li><a href="./python/randint.html">Random integer</a></li>
@ -415,7 +415,7 @@
<li><a href="./python/Reading_data_from_a_sql_database_with_pandas.html">Reading data from a sql database with pandas</a></li> <li><a href="./python/Reading_data_from_a_sql_database_with_pandas.html">Reading data from a sql database with pandas</a></li>
<li><a href="./python/Writing_data_to_a_sql_database_with_pandas.html">Writing data to a sql database with pandas</a></li> <li><a href="./python/Writing_data_to_a_sql_database_with_pandas.html">Writing data to a sql database with pandas</a></li>
<li><a href="./python/Creating_a_sqlite_database.html">Creating a sqlite database</a></li> <li><a href="./python/Creating_a_sqlite_database.html">Creating a sqlite database</a></li>
<li><a href="./python/Iterating_over_a_dataframe.html">Iterating over a DataFrame</a></li> <li><a href="./python/Iterating_over_a_dataframe.html">Iterate over a DataFrame</a></li>
</ul> </ul>
</div> </div>
</div> </div>
@ -493,8 +493,10 @@
</div> </div>
<div class="panel-body"> <div class="panel-body">
<ul> <ul>
<li><a href="./python/compare_dict.html">Get items in one dictionnary but not the other one</a></li>
<li><a href="./python/maximize_window.html">Maximize a window in Windows</a></li> <li><a href="./python/maximize_window.html">Maximize a window in Windows</a></li>
<li><a href="./python/iterate_dict.html">Iterate over a dictionnary</a></li> <li><a href="./python/case_config.html">Case sensitive ConfigParser</a></li>
<li><a href="./python/list_windows.html">List all opened windows on Windows</a></li>
<li><a href="./python/Optimized_numpy_random_intel.html">Optimized numpy random number generation on Intel CPU</a></li> <li><a href="./python/Optimized_numpy_random_intel.html">Optimized numpy random number generation on Intel CPU</a></li>
<li><a href="./python/updating_all_python_package_with_anaconda.html">Updating all python package with anaconda</a></li> <li><a href="./python/updating_all_python_package_with_anaconda.html">Updating all python package with anaconda</a></li>
</ul> </ul>
@ -708,7 +710,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 92 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
jupyter/clear_cell.html
View File

@ -149,7 +149,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
linux/bashrc.html
View File

@ -203,7 +203,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
linux/directory_size.html
View File

@ -148,7 +148,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
linux/free_disk_space_linux.html
View File

@ -167,7 +167,7 @@ none 0 0 0 - /config
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
linux/get_ip_linux.html
View File

@ -256,7 +256,7 @@ wifi0 Link encap:UNSPEC HWaddr 5C-51-4F-41-7A-AD-00-00-00-00-00-00-00-00-00
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
linux/linux_process_information.html
View File

@ -172,7 +172,7 @@ USER;PID;%CPU;%MEM;VSZ;RSS;TTY;STAT;START;TIME;COMMAND</p>
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

14
linux/ramdisk.html
View File

@ -132,9 +132,9 @@
<p>On my machine with a ssd I get the following results</p> <p>On my machine with a ssd I get the following results</p>
<div class="highlight"><pre><span></span>500+0 records in <div class="highlight"><pre><span></span><span class="mi">500</span><span class="o">+</span><span class="mi">0</span> <span class="n">records</span> <span class="k">in</span>
500+0 records out <span class="mi">500</span><span class="o">+</span><span class="mi">0</span> <span class="n">records</span> <span class="k">out</span>
524288000 bytes (524 MB, 500 MiB) copied, 10,153 s, 51,6 MB/s <span class="mi">524288000</span> <span class="n">bytes</span> <span class="p">(</span><span class="mi">524</span> <span class="n">MB</span><span class="p">,</span> <span class="mi">500</span> <span class="n">MiB</span><span class="p">)</span> <span class="n">copied</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span><span class="mi">153</span> <span class="n">s</span><span class="p">,</span> <span class="mi">51</span><span class="p">,</span><span class="mi">6</span> <span class="n">MB</span><span class="o">/</span><span class="n">s</span>
</pre></div> </pre></div>
@ -148,9 +148,9 @@ dd <span class="k">if</span><span class="o">=</span>/dev/zero <span class="nv">o
<p>The results yield a faster write time : </p> <p>The results yield a faster write time : </p>
<div class="highlight"><pre><span></span>500+0 records in <div class="highlight"><pre><span></span><span class="mi">500</span><span class="o">+</span><span class="mi">0</span> <span class="n">records</span> <span class="k">in</span>
500+0 records out <span class="mi">500</span><span class="o">+</span><span class="mi">0</span> <span class="n">records</span> <span class="k">out</span>
524288000 bytes (524 MB, 500 MiB) copied, 6,39849 s, 81,9 MB/s <span class="mi">524288000</span> <span class="n">bytes</span> <span class="p">(</span><span class="mi">524</span> <span class="n">MB</span><span class="p">,</span> <span class="mi">500</span> <span class="n">MiB</span><span class="p">)</span> <span class="n">copied</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span><span class="mi">39849</span> <span class="n">s</span><span class="p">,</span> <span class="mi">81</span><span class="p">,</span><span class="mi">9</span> <span class="n">MB</span><span class="o">/</span><span class="n">s</span>
</pre></div> </pre></div>
@ -169,7 +169,7 @@ dd <span class="k">if</span><span class="o">=</span>/dev/zero <span class="nv">o
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

482
linux/sed.html
View File

@ -130,59 +130,59 @@
* deleting * deleting
* printing </p> * printing </p>
<p>For this example we will learn how to remove the comments starting with the '#' sign and the blank lines for the following file :</p> <p>For this example we will learn how to remove the comments starting with the '#' sign and the blank lines for the following file :</p>
<div class="highlight"><pre><span></span>## Header of input.csv <div class="highlight"><pre><span></span>## <span class="nv">Header</span> <span class="nv">of</span> <span class="nv">input</span>.<span class="nv">csv</span>
#this file contains information I want to parse with a simple program. #<span class="nv">this</span> <span class="nv">file</span> <span class="nv">contains</span> <span class="nv">information</span> <span class="nv">I</span> <span class="nv">want</span> <span class="nv">to</span> <span class="nv">parse</span> <span class="nv">with</span> <span class="nv">a</span> <span class="nv">simple</span> <span class="nv">program</span>.
#The header, the footer or any comment starting with a &quot;#&quot; will be removed #<span class="nv">The</span> <span class="nv">header</span>, <span class="nv">the</span> <span class="nv">footer</span> <span class="nv">or</span> <span class="nv">any</span> <span class="nv">comment</span> <span class="nv">starting</span> <span class="nv">with</span> <span class="nv">a</span> <span class="s2">&quot;</span><span class="s">#</span><span class="s2">&quot;</span> <span class="nv">will</span> <span class="nv">be</span> <span class="nv">removed</span>
#The blank lines will also be removed #<span class="nv">The</span> <span class="nv">blank</span> <span class="nv">lines</span> <span class="nv">will</span> <span class="nv">also</span> <span class="nv">be</span> <span class="nv">removed</span>
#img,processed,defaut #<span class="nv">img</span>,<span class="nv">processed</span>,<span class="nv">defaut</span>
#bloc 1 #<span class="nv">bloc</span> <span class="mi">1</span>
0,a0000.tif,, <span class="mi">0</span>,<span class="nv">a0000</span>.<span class="nv">tif</span>,,
1,a0001.tif,True,&quot;(139, 63)(145, 91)&quot; <span class="mi">1</span>,<span class="nv">a0001</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(139, 63)(145, 91)</span><span class="s2">&quot;</span>
2,a0002.tif,True,&quot;(93, 72)(24, 162)(31, 64)&quot; <span class="mi">2</span>,<span class="nv">a0002</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(93, 72)(24, 162)(31, 64)</span><span class="s2">&quot;</span>
3,a0003.tif,, <span class="mi">3</span>,<span class="nv">a0003</span>.<span class="nv">tif</span>,,
4,a0004.tif,, <span class="mi">4</span>,<span class="nv">a0004</span>.<span class="nv">tif</span>,,
5,a0005.tif,, <span class="mi">5</span>,<span class="nv">a0005</span>.<span class="nv">tif</span>,,
6,a0006.tif,, <span class="mi">6</span>,<span class="nv">a0006</span>.<span class="nv">tif</span>,,
7,a0007.tif,, <span class="mi">7</span>,<span class="nv">a0007</span>.<span class="nv">tif</span>,,
8,a0008.tif,, <span class="mi">8</span>,<span class="nv">a0008</span>.<span class="nv">tif</span>,,
9,a0009.tif,True,&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot; <span class="mi">9</span>,<span class="nv">a0009</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)</span><span class="s2">&quot;</span>
10,a0010.tif,, <span class="mi">10</span>,<span class="nv">a0010</span>.<span class="nv">tif</span>,,
11,a0011.tif,True,&quot;(39, 78)(84, 110)&quot; # a random comment passing by <span class="mi">11</span>,<span class="nv">a0011</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(39, 78)(84, 110)</span><span class="s2">&quot;</span> # <span class="nv">a</span> <span class="k">random</span> <span class="nv">comment</span> <span class="nv">passing</span> <span class="nv">by</span>
#end of bloc 1 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">1</span>
#bloc 2 #<span class="nv">bloc</span> <span class="mi">2</span>
12,a0012.tif,, <span class="mi">12</span>,<span class="nv">a0012</span>.<span class="nv">tif</span>,,
13,a0013.tif,, <span class="mi">13</span>,<span class="nv">a0013</span>.<span class="nv">tif</span>,,
14,a0014.tif,, <span class="mi">14</span>,<span class="nv">a0014</span>.<span class="nv">tif</span>,,
15,a0015.tif,True,&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot; <span class="mi">15</span>,<span class="nv">a0015</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(146, 65)(146, 89)(139, 146)(16, 68)</span><span class="s2">&quot;</span>
16,a0016.tif,True,&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot; <span class="mi">16</span>,<span class="nv">a0016</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)</span><span class="s2">&quot;</span>
17,a0017.tif,, <span class="mi">17</span>,<span class="nv">a0017</span>.<span class="nv">tif</span>,,
#end of bloc 2 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">2</span>
#bloc 3 #<span class="nv">bloc</span> <span class="mi">3</span>
18,a0018.tif,, <span class="mi">18</span>,<span class="nv">a0018</span>.<span class="nv">tif</span>,,
19,a0019.tif,, <span class="mi">19</span>,<span class="nv">a0019</span>.<span class="nv">tif</span>,,
20,a0020.tif,True,&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot; <span class="mi">20</span>,<span class="nv">a0020</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(57, 99)(12, 113)(27, 139)(16, 158)</span><span class="s2">&quot;</span>
21,a0021.tif,, <span class="mi">21</span>,<span class="nv">a0021</span>.<span class="nv">tif</span>,,
22,a0022.tif,, <span class="mi">22</span>,<span class="nv">a0022</span>.<span class="nv">tif</span>,,
23,a0023.tif,, <span class="mi">23</span>,<span class="nv">a0023</span>.<span class="nv">tif</span>,,
24,a0024.tif,, <span class="mi">24</span>,<span class="nv">a0024</span>.<span class="nv">tif</span>,,
25,a0025.tif,, <span class="mi">25</span>,<span class="nv">a0025</span>.<span class="nv">tif</span>,,
26,a0026.tif,, <span class="mi">26</span>,<span class="nv">a0026</span>.<span class="nv">tif</span>,,
#end of bloc 3 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">3</span>
27,a0027.tif,True,&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot; <span class="mi">27</span>,<span class="nv">a0027</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)</span><span class="s2">&quot;</span>
28,a0028.tif,, <span class="mi">28</span>,<span class="nv">a0028</span>.<span class="nv">tif</span>,,
29,a0029.tif,True,&quot;(128, 58)&quot; <span class="mi">29</span>,<span class="nv">a0029</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(128, 58)</span><span class="s2">&quot;</span>
30,a0030.tif,True,&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot; <span class="mi">30</span>,<span class="nv">a0030</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(133, 59)(99, 77)(111, 100)(115, 153)</span><span class="s2">&quot;</span>
31,a0031.tif,True,&quot;(43, 154)(27, 177)&quot; <span class="mi">31</span>,<span class="nv">a0031</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(43, 154)(27, 177)</span><span class="s2">&quot;</span>
## footer : end of file ## <span class="nv">footer</span> : <span class="k">end</span> <span class="nv">of</span> <span class="nv">file</span>
</pre></div> </pre></div>
@ -201,59 +201,59 @@
<p>so we have <code>s</code> meaning that we want to use the replace command followed by a <code>/</code> and the caracter(s) we want to replace followed by a <code>/</code> and the caracter(s) we want to replace it with and finally a <code>/</code>.</p> <p>so we have <code>s</code> meaning that we want to use the replace command followed by a <code>/</code> and the caracter(s) we want to replace followed by a <code>/</code> and the caracter(s) we want to replace it with and finally a <code>/</code>.</p>
<p>The result is the following :</p> <p>The result is the following :</p>
<div class="highlight"><pre><span></span>## Header <div class="highlight"><pre><span></span>## <span class="nv">Header</span>
#this file contains information I want to parse with a simple program. #<span class="nv">this</span> <span class="nv">file</span> <span class="nv">contains</span> <span class="nv">information</span> <span class="nv">I</span> <span class="nv">want</span> <span class="nv">to</span> <span class="nv">parse</span> <span class="nv">with</span> <span class="nv">a</span> <span class="nv">simple</span> <span class="nv">program</span>.
#The header; the footer or any comment starting with a &quot;#&quot; will be removed #<span class="nv">The</span> <span class="nv">header</span><span class="c1">; the footer or any comment starting with a &quot;#&quot; will be removed</span>
#The blank lines will also be removed #<span class="nv">The</span> <span class="nv">blank</span> <span class="nv">lines</span> <span class="nv">will</span> <span class="nv">also</span> <span class="nv">be</span> <span class="nv">removed</span>
#img;processed,defaut #<span class="nv">img</span><span class="c1">;processed,defaut</span>
#bloc 1 #<span class="nv">bloc</span> <span class="mi">1</span>
0;a0000.tif,, <span class="mi">0</span><span class="c1">;a0000.tif,,</span>
1;a0001.tif,True,&quot;(139, 63)(145, 91)&quot; <span class="mi">1</span><span class="c1">;a0001.tif,True,&quot;(139, 63)(145, 91)&quot;</span>
2;a0002.tif,True,&quot;(93, 72)(24, 162)(31, 64)&quot; <span class="mi">2</span><span class="c1">;a0002.tif,True,&quot;(93, 72)(24, 162)(31, 64)&quot;</span>
3;a0003.tif,, <span class="mi">3</span><span class="c1">;a0003.tif,,</span>
4;a0004.tif,, <span class="mi">4</span><span class="c1">;a0004.tif,,</span>
5;a0005.tif,, <span class="mi">5</span><span class="c1">;a0005.tif,,</span>
6;a0006.tif,, <span class="mi">6</span><span class="c1">;a0006.tif,,</span>
7;a0007.tif,, <span class="mi">7</span><span class="c1">;a0007.tif,,</span>
8;a0008.tif,, <span class="mi">8</span><span class="c1">;a0008.tif,,</span>
9;a0009.tif,True,&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot; <span class="mi">9</span><span class="c1">;a0009.tif,True,&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot;</span>
10;a0010.tif,, <span class="mi">10</span><span class="c1">;a0010.tif,,</span>
11;a0011.tif,True,&quot;(39, 78)(84, 110)&quot; # a random comment passing by <span class="mi">11</span><span class="c1">;a0011.tif,True,&quot;(39, 78)(84, 110)&quot; # a random comment passing by</span>
#end of bloc 1 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">1</span>
#bloc 2 #<span class="nv">bloc</span> <span class="mi">2</span>
12;a0012.tif,, <span class="mi">12</span><span class="c1">;a0012.tif,,</span>
13;a0013.tif,, <span class="mi">13</span><span class="c1">;a0013.tif,,</span>
14;a0014.tif,, <span class="mi">14</span><span class="c1">;a0014.tif,,</span>
15;a0015.tif,True,&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot; <span class="mi">15</span><span class="c1">;a0015.tif,True,&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot;</span>
16;a0016.tif,True,&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot; <span class="mi">16</span><span class="c1">;a0016.tif,True,&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot;</span>
17;a0017.tif,, <span class="mi">17</span><span class="c1">;a0017.tif,,</span>
#end of bloc 2 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">2</span>
#bloc 3 #<span class="nv">bloc</span> <span class="mi">3</span>
18;a0018.tif,, <span class="mi">18</span><span class="c1">;a0018.tif,,</span>
19;a0019.tif,, <span class="mi">19</span><span class="c1">;a0019.tif,,</span>
20;a0020.tif,True,&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot; <span class="mi">20</span><span class="c1">;a0020.tif,True,&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot;</span>
21;a0021.tif,, <span class="mi">21</span><span class="c1">;a0021.tif,,</span>
22;a0022.tif,, <span class="mi">22</span><span class="c1">;a0022.tif,,</span>
23;a0023.tif,, <span class="mi">23</span><span class="c1">;a0023.tif,,</span>
24;a0024.tif,, <span class="mi">24</span><span class="c1">;a0024.tif,,</span>
25;a0025.tif,, <span class="mi">25</span><span class="c1">;a0025.tif,,</span>
26;a0026.tif,, <span class="mi">26</span><span class="c1">;a0026.tif,,</span>
#end of bloc 3 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">3</span>
27;a0027.tif,True,&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot; <span class="mi">27</span><span class="c1">;a0027.tif,True,&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot;</span>
28;a0028.tif,, <span class="mi">28</span><span class="c1">;a0028.tif,,</span>
29;a0029.tif,True,&quot;(128, 58)&quot; <span class="mi">29</span><span class="c1">;a0029.tif,True,&quot;(128, 58)&quot;</span>
30;a0030.tif,True,&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot; <span class="mi">30</span><span class="c1">;a0030.tif,True,&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot;</span>
31;a0031.tif,True,&quot;(43, 154)(27, 177)&quot; <span class="mi">31</span><span class="c1">;a0031.tif,True,&quot;(43, 154)(27, 177)&quot;</span>
## footer : end of file ## <span class="nv">footer</span> : <span class="k">end</span> <span class="nv">of</span> <span class="nv">file</span>
</pre></div> </pre></div>
@ -262,59 +262,59 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>## Header <div class="highlight"><pre><span></span>## <span class="nv">Header</span>
#this file contains information I want to parse with a simple program. #<span class="nv">this</span> <span class="nv">file</span> <span class="nv">contains</span> <span class="nv">information</span> <span class="nv">I</span> <span class="nv">want</span> <span class="nv">to</span> <span class="nv">parse</span> <span class="nv">with</span> <span class="nv">a</span> <span class="nv">simple</span> <span class="nv">program</span>.
#The header; the footer or any comment starting with a &quot;#&quot; will be removed #<span class="nv">The</span> <span class="nv">header</span><span class="c1">; the footer or any comment starting with a &quot;#&quot; will be removed</span>
#The blank lines will also be removed #<span class="nv">The</span> <span class="nv">blank</span> <span class="nv">lines</span> <span class="nv">will</span> <span class="nv">also</span> <span class="nv">be</span> <span class="nv">removed</span>
#img;processed;defaut #<span class="nv">img</span><span class="c1">;processed;defaut</span>
#bloc 1 #<span class="nv">bloc</span> <span class="mi">1</span>
0;a0000.tif;; <span class="mi">0</span><span class="c1">;a0000.tif;;</span>
1;a0001.tif;True;&quot;(139; 63)(145; 91)&quot; <span class="mi">1</span><span class="c1">;a0001.tif;True;&quot;(139; 63)(145; 91)&quot;</span>
2;a0002.tif;True;&quot;(93; 72)(24; 162)(31; 64)&quot; <span class="mi">2</span><span class="c1">;a0002.tif;True;&quot;(93; 72)(24; 162)(31; 64)&quot;</span>
3;a0003.tif;; <span class="mi">3</span><span class="c1">;a0003.tif;;</span>
4;a0004.tif;; <span class="mi">4</span><span class="c1">;a0004.tif;;</span>
5;a0005.tif;; <span class="mi">5</span><span class="c1">;a0005.tif;;</span>
6;a0006.tif;; <span class="mi">6</span><span class="c1">;a0006.tif;;</span>
7;a0007.tif;; <span class="mi">7</span><span class="c1">;a0007.tif;;</span>
8;a0008.tif;; <span class="mi">8</span><span class="c1">;a0008.tif;;</span>
9;a0009.tif;True;&quot;(127; 80)(104; 60)(87; 63)(53; 78)(17; 126)&quot; <span class="mi">9</span><span class="c1">;a0009.tif;True;&quot;(127; 80)(104; 60)(87; 63)(53; 78)(17; 126)&quot;</span>
10;a0010.tif;; <span class="mi">10</span><span class="c1">;a0010.tif;;</span>
11;a0011.tif;True;&quot;(39; 78)(84; 110)&quot; # a random comment passing by <span class="mi">11</span><span class="c1">;a0011.tif;True;&quot;(39; 78)(84; 110)&quot; # a random comment passing by</span>
#end of bloc 1 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">1</span>
#bloc 2 #<span class="nv">bloc</span> <span class="mi">2</span>
12;a0012.tif;; <span class="mi">12</span><span class="c1">;a0012.tif;;</span>
13;a0013.tif;; <span class="mi">13</span><span class="c1">;a0013.tif;;</span>
14;a0014.tif;; <span class="mi">14</span><span class="c1">;a0014.tif;;</span>
15;a0015.tif;True;&quot;(146; 65)(146; 89)(139; 146)(16; 68)&quot; <span class="mi">15</span><span class="c1">;a0015.tif;True;&quot;(146; 65)(146; 89)(139; 146)(16; 68)&quot;</span>
16;a0016.tif;True;&quot;(51; 59)(77; 69)(145; 78)(139; 112)(97; 123)(17; 148)&quot; <span class="mi">16</span><span class="c1">;a0016.tif;True;&quot;(51; 59)(77; 69)(145; 78)(139; 112)(97; 123)(17; 148)&quot;</span>
17;a0017.tif;; <span class="mi">17</span><span class="c1">;a0017.tif;;</span>
#end of bloc 2 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">2</span>
#bloc 3 #<span class="nv">bloc</span> <span class="mi">3</span>
18;a0018.tif;; <span class="mi">18</span><span class="c1">;a0018.tif;;</span>
19;a0019.tif;; <span class="mi">19</span><span class="c1">;a0019.tif;;</span>
20;a0020.tif;True;&quot;(57; 99)(12; 113)(27; 139)(16; 158)&quot; <span class="mi">20</span><span class="c1">;a0020.tif;True;&quot;(57; 99)(12; 113)(27; 139)(16; 158)&quot;</span>
21;a0021.tif;; <span class="mi">21</span><span class="c1">;a0021.tif;;</span>
22;a0022.tif;; <span class="mi">22</span><span class="c1">;a0022.tif;;</span>
23;a0023.tif;; <span class="mi">23</span><span class="c1">;a0023.tif;;</span>
24;a0024.tif;; <span class="mi">24</span><span class="c1">;a0024.tif;;</span>
25;a0025.tif;; <span class="mi">25</span><span class="c1">;a0025.tif;;</span>
26;a0026.tif;; <span class="mi">26</span><span class="c1">;a0026.tif;;</span>
#end of bloc 3 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">3</span>
27;a0027.tif;True;&quot;(11; 86)(29; 74)(92; 68)(109; 129)(132; 104)&quot; <span class="mi">27</span><span class="c1">;a0027.tif;True;&quot;(11; 86)(29; 74)(92; 68)(109; 129)(132; 104)&quot;</span>
28;a0028.tif;; <span class="mi">28</span><span class="c1">;a0028.tif;;</span>
29;a0029.tif;True;&quot;(128; 58)&quot; <span class="mi">29</span><span class="c1">;a0029.tif;True;&quot;(128; 58)&quot;</span>
30;a0030.tif;True;&quot;(133; 59)(99; 77)(111; 100)(115; 153)&quot; <span class="mi">30</span><span class="c1">;a0030.tif;True;&quot;(133; 59)(99; 77)(111; 100)(115; 153)&quot;</span>
31;a0031.tif;True;&quot;(43; 154)(27; 177)&quot; <span class="mi">31</span><span class="c1">;a0031.tif;True;&quot;(43; 154)(27; 177)&quot;</span>
## footer : end of file ## <span class="nv">footer</span> : <span class="k">end</span> <span class="nv">of</span> <span class="nv">file</span>
</pre></div> </pre></div>
@ -333,49 +333,49 @@
<p>If we run that command, all our comments have disappeared </p> <p>If we run that command, all our comments have disappeared </p>
<div class="highlight"><pre><span></span>0,a0000.tif,, <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">,</span><span class="n">a0000</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
1,a0001.tif,True,&quot;(139, 63)(145, 91)&quot; <span class="mi">1</span><span class="p">,</span><span class="n">a0001</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(139, 63)(145, 91)&quot;</span>
2,a0002.tif,True,&quot;(93, 72)(24, 162)(31, 64)&quot; <span class="mi">2</span><span class="p">,</span><span class="n">a0002</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(93, 72)(24, 162)(31, 64)&quot;</span>
3,a0003.tif,, <span class="mi">3</span><span class="p">,</span><span class="n">a0003</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
4,a0004.tif,, <span class="mi">4</span><span class="p">,</span><span class="n">a0004</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
5,a0005.tif,, <span class="mi">5</span><span class="p">,</span><span class="n">a0005</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
6,a0006.tif,, <span class="mi">6</span><span class="p">,</span><span class="n">a0006</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
7,a0007.tif,, <span class="mi">7</span><span class="p">,</span><span class="n">a0007</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
8,a0008.tif,, <span class="mi">8</span><span class="p">,</span><span class="n">a0008</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
9,a0009.tif,True,&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot; <span class="mi">9</span><span class="p">,</span><span class="n">a0009</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot;</span>
10,a0010.tif,, <span class="mi">10</span><span class="p">,</span><span class="n">a0010</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
11,a0011.tif,True,&quot;(39, 78)(84, 110)&quot; <span class="mi">11</span><span class="p">,</span><span class="n">a0011</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(39, 78)(84, 110)&quot;</span>
12,a0012.tif,, <span class="mi">12</span><span class="p">,</span><span class="n">a0012</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
13,a0013.tif,, <span class="mi">13</span><span class="p">,</span><span class="n">a0013</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
14,a0014.tif,, <span class="mi">14</span><span class="p">,</span><span class="n">a0014</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
15,a0015.tif,True,&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot; <span class="mi">15</span><span class="p">,</span><span class="n">a0015</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot;</span>
16,a0016.tif,True,&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot; <span class="mi">16</span><span class="p">,</span><span class="n">a0016</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot;</span>
17,a0017.tif,, <span class="mi">17</span><span class="p">,</span><span class="n">a0017</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
18,a0018.tif,, <span class="mi">18</span><span class="p">,</span><span class="n">a0018</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
19,a0019.tif,, <span class="mi">19</span><span class="p">,</span><span class="n">a0019</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
20,a0020.tif,True,&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot; <span class="mi">20</span><span class="p">,</span><span class="n">a0020</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot;</span>
21,a0021.tif,, <span class="mi">21</span><span class="p">,</span><span class="n">a0021</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
22,a0022.tif,, <span class="mi">22</span><span class="p">,</span><span class="n">a0022</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
23,a0023.tif,, <span class="mi">23</span><span class="p">,</span><span class="n">a0023</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
24,a0024.tif,, <span class="mi">24</span><span class="p">,</span><span class="n">a0024</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
25,a0025.tif,, <span class="mi">25</span><span class="p">,</span><span class="n">a0025</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
26,a0026.tif,, <span class="mi">26</span><span class="p">,</span><span class="n">a0026</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
27,a0027.tif,True,&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot; <span class="mi">27</span><span class="p">,</span><span class="n">a0027</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot;</span>
28,a0028.tif,, <span class="mi">28</span><span class="p">,</span><span class="n">a0028</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
29,a0029.tif,True,&quot;(128, 58)&quot; <span class="mi">29</span><span class="p">,</span><span class="n">a0029</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(128, 58)&quot;</span>
30,a0030.tif,True,&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot; <span class="mi">30</span><span class="p">,</span><span class="n">a0030</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot;</span>
31,a0031.tif,True,&quot;(43, 154)(27, 177)&quot; <span class="mi">31</span><span class="p">,</span><span class="n">a0031</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(43, 154)(27, 177)&quot;</span>
</pre></div> </pre></div>
@ -387,50 +387,50 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>## Header <div class="highlight"><pre><span></span>## <span class="nv">Header</span>
#this file contains information I want to parse with a simple program. #<span class="nv">this</span> <span class="nv">file</span> <span class="nv">contains</span> <span class="nv">information</span> <span class="nv">I</span> <span class="nv">want</span> <span class="nv">to</span> <span class="nv">parse</span> <span class="nv">with</span> <span class="nv">a</span> <span class="nv">simple</span> <span class="nv">program</span>.
#The header, the footer or any comment starting with a &quot;#&quot; will be removed #<span class="nv">The</span> <span class="nv">header</span>, <span class="nv">the</span> <span class="nv">footer</span> <span class="nv">or</span> <span class="nv">any</span> <span class="nv">comment</span> <span class="nv">starting</span> <span class="nv">with</span> <span class="nv">a</span> <span class="s2">&quot;</span><span class="s">#</span><span class="s2">&quot;</span> <span class="nv">will</span> <span class="nv">be</span> <span class="nv">removed</span>
#The blank lines will also be removed #<span class="nv">The</span> <span class="nv">blank</span> <span class="nv">lines</span> <span class="nv">will</span> <span class="nv">also</span> <span class="nv">be</span> <span class="nv">removed</span>
#img,processed,defaut #<span class="nv">img</span>,<span class="nv">processed</span>,<span class="nv">defaut</span>
#bloc 1 #<span class="nv">bloc</span> <span class="mi">1</span>
0,a0000.tif,, <span class="mi">0</span>,<span class="nv">a0000</span>.<span class="nv">tif</span>,,
1,a0001.tif,True,&quot;(139, 63)(145, 91)&quot; <span class="mi">1</span>,<span class="nv">a0001</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(139, 63)(145, 91)</span><span class="s2">&quot;</span>
2,a0002.tif,True,&quot;(93, 72)(24, 162)(31, 64)&quot; <span class="mi">2</span>,<span class="nv">a0002</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(93, 72)(24, 162)(31, 64)</span><span class="s2">&quot;</span>
3,a0003.tif,, <span class="mi">3</span>,<span class="nv">a0003</span>.<span class="nv">tif</span>,,
4,a0004.tif,, <span class="mi">4</span>,<span class="nv">a0004</span>.<span class="nv">tif</span>,,
5,a0005.tif,, <span class="mi">5</span>,<span class="nv">a0005</span>.<span class="nv">tif</span>,,
6,a0006.tif,, <span class="mi">6</span>,<span class="nv">a0006</span>.<span class="nv">tif</span>,,
7,a0007.tif,, <span class="mi">7</span>,<span class="nv">a0007</span>.<span class="nv">tif</span>,,
8,a0008.tif,, <span class="mi">8</span>,<span class="nv">a0008</span>.<span class="nv">tif</span>,,
9,a0009.tif,True,&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot; <span class="mi">9</span>,<span class="nv">a0009</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)</span><span class="s2">&quot;</span>
10,a0010.tif,, <span class="mi">10</span>,<span class="nv">a0010</span>.<span class="nv">tif</span>,,
11,a0011.tif,True,&quot;(39, 78)(84, 110)&quot; # a random comment passing by <span class="mi">11</span>,<span class="nv">a0011</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(39, 78)(84, 110)</span><span class="s2">&quot;</span> # <span class="nv">a</span> <span class="k">random</span> <span class="nv">comment</span> <span class="nv">passing</span> <span class="nv">by</span>
#end of bloc 1 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">1</span>
#bloc 2 #<span class="nv">bloc</span> <span class="mi">2</span>
12,a0012.tif,, <span class="mi">12</span>,<span class="nv">a0012</span>.<span class="nv">tif</span>,,
13,a0013.tif,, <span class="mi">13</span>,<span class="nv">a0013</span>.<span class="nv">tif</span>,,
14,a0014.tif,, <span class="mi">14</span>,<span class="nv">a0014</span>.<span class="nv">tif</span>,,
15,a0015.tif,True,&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot; <span class="mi">15</span>,<span class="nv">a0015</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(146, 65)(146, 89)(139, 146)(16, 68)</span><span class="s2">&quot;</span>
16,a0016.tif,True,&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot; <span class="mi">16</span>,<span class="nv">a0016</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)</span><span class="s2">&quot;</span>
17,a0017.tif,, <span class="mi">17</span>,<span class="nv">a0017</span>.<span class="nv">tif</span>,,
#end of bloc 2 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">2</span>
#bloc 3 #<span class="nv">bloc</span> <span class="mi">3</span>
18,a0018.tif,, <span class="mi">18</span>,<span class="nv">a0018</span>.<span class="nv">tif</span>,,
19,a0019.tif,, <span class="mi">19</span>,<span class="nv">a0019</span>.<span class="nv">tif</span>,,
20,a0020.tif,True,&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot; <span class="mi">20</span>,<span class="nv">a0020</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(57, 99)(12, 113)(27, 139)(16, 158)</span><span class="s2">&quot;</span>
21,a0021.tif,, <span class="mi">21</span>,<span class="nv">a0021</span>.<span class="nv">tif</span>,,
22,a0022.tif,, <span class="mi">22</span>,<span class="nv">a0022</span>.<span class="nv">tif</span>,,
23,a0023.tif,, <span class="mi">23</span>,<span class="nv">a0023</span>.<span class="nv">tif</span>,,
24,a0024.tif,, <span class="mi">24</span>,<span class="nv">a0024</span>.<span class="nv">tif</span>,,
25,a0025.tif,, <span class="mi">25</span>,<span class="nv">a0025</span>.<span class="nv">tif</span>,,
26,a0026.tif,, <span class="mi">26</span>,<span class="nv">a0026</span>.<span class="nv">tif</span>,,
#end of bloc 3 #<span class="k">end</span> <span class="nv">of</span> <span class="nv">bloc</span> <span class="mi">3</span>
27,a0027.tif,True,&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot; <span class="mi">27</span>,<span class="nv">a0027</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)</span><span class="s2">&quot;</span>
28,a0028.tif,, <span class="mi">28</span>,<span class="nv">a0028</span>.<span class="nv">tif</span>,,
29,a0029.tif,True,&quot;(128, 58)&quot; <span class="mi">29</span>,<span class="nv">a0029</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(128, 58)</span><span class="s2">&quot;</span>
30,a0030.tif,True,&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot; <span class="mi">30</span>,<span class="nv">a0030</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(133, 59)(99, 77)(111, 100)(115, 153)</span><span class="s2">&quot;</span>
31,a0031.tif,True,&quot;(43, 154)(27, 177)&quot; <span class="mi">31</span>,<span class="nv">a0031</span>.<span class="nv">tif</span>,<span class="nv">True</span>,<span class="s2">&quot;</span><span class="s">(43, 154)(27, 177)</span><span class="s2">&quot;</span>
## footer : end of file ## <span class="nv">footer</span> : <span class="k">end</span> <span class="nv">of</span> <span class="nv">file</span>
</pre></div> </pre></div>
@ -441,38 +441,38 @@
<p>and the final output is </p> <p>and the final output is </p>
<div class="highlight"><pre><span></span>0,a0000.tif,, <div class="highlight"><pre><span></span><span class="mi">0</span><span class="p">,</span><span class="n">a0000</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
1,a0001.tif,True,&quot;(139, 63)(145, 91)&quot; <span class="mi">1</span><span class="p">,</span><span class="n">a0001</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(139, 63)(145, 91)&quot;</span>
2,a0002.tif,True,&quot;(93, 72)(24, 162)(31, 64)&quot; <span class="mi">2</span><span class="p">,</span><span class="n">a0002</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(93, 72)(24, 162)(31, 64)&quot;</span>
3,a0003.tif,, <span class="mi">3</span><span class="p">,</span><span class="n">a0003</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
4,a0004.tif,, <span class="mi">4</span><span class="p">,</span><span class="n">a0004</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
5,a0005.tif,, <span class="mi">5</span><span class="p">,</span><span class="n">a0005</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
6,a0006.tif,, <span class="mi">6</span><span class="p">,</span><span class="n">a0006</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
7,a0007.tif,, <span class="mi">7</span><span class="p">,</span><span class="n">a0007</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
8,a0008.tif,, <span class="mi">8</span><span class="p">,</span><span class="n">a0008</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
9,a0009.tif,True,&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot; <span class="mi">9</span><span class="p">,</span><span class="n">a0009</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(127, 80)(104, 60)(87, 63)(53, 78)(17, 126)&quot;</span>
10,a0010.tif,, <span class="mi">10</span><span class="p">,</span><span class="n">a0010</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
11,a0011.tif,True,&quot;(39, 78)(84, 110)&quot; <span class="mi">11</span><span class="p">,</span><span class="n">a0011</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(39, 78)(84, 110)&quot;</span>
12,a0012.tif,, <span class="mi">12</span><span class="p">,</span><span class="n">a0012</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
13,a0013.tif,, <span class="mi">13</span><span class="p">,</span><span class="n">a0013</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
14,a0014.tif,, <span class="mi">14</span><span class="p">,</span><span class="n">a0014</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
15,a0015.tif,True,&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot; <span class="mi">15</span><span class="p">,</span><span class="n">a0015</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(146, 65)(146, 89)(139, 146)(16, 68)&quot;</span>
16,a0016.tif,True,&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot; <span class="mi">16</span><span class="p">,</span><span class="n">a0016</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(51, 59)(77, 69)(145, 78)(139, 112)(97, 123)(17, 148)&quot;</span>
17,a0017.tif,, <span class="mi">17</span><span class="p">,</span><span class="n">a0017</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
18,a0018.tif,, <span class="mi">18</span><span class="p">,</span><span class="n">a0018</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
19,a0019.tif,, <span class="mi">19</span><span class="p">,</span><span class="n">a0019</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
20,a0020.tif,True,&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot; <span class="mi">20</span><span class="p">,</span><span class="n">a0020</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(57, 99)(12, 113)(27, 139)(16, 158)&quot;</span>
21,a0021.tif,, <span class="mi">21</span><span class="p">,</span><span class="n">a0021</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
22,a0022.tif,, <span class="mi">22</span><span class="p">,</span><span class="n">a0022</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
23,a0023.tif,, <span class="mi">23</span><span class="p">,</span><span class="n">a0023</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
24,a0024.tif,, <span class="mi">24</span><span class="p">,</span><span class="n">a0024</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
25,a0025.tif,, <span class="mi">25</span><span class="p">,</span><span class="n">a0025</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
26,a0026.tif,, <span class="mi">26</span><span class="p">,</span><span class="n">a0026</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
27,a0027.tif,True,&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot; <span class="mi">27</span><span class="p">,</span><span class="n">a0027</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(11, 86)(29, 74)(92, 68)(109, 129)(132, 104)&quot;</span>
28,a0028.tif,, <span class="mi">28</span><span class="p">,</span><span class="n">a0028</span><span class="p">.</span><span class="n">tif</span><span class="p">,,</span>
29,a0029.tif,True,&quot;(128, 58)&quot; <span class="mi">29</span><span class="p">,</span><span class="n">a0029</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(128, 58)&quot;</span>
30,a0030.tif,True,&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot; <span class="mi">30</span><span class="p">,</span><span class="n">a0030</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(133, 59)(99, 77)(111, 100)(115, 153)&quot;</span>
31,a0031.tif,True,&quot;(43, 154)(27, 177)&quot; <span class="mi">31</span><span class="p">,</span><span class="n">a0031</span><span class="p">.</span><span class="n">tif</span><span class="p">,</span><span class="k">True</span><span class="p">,</span><span class="ss">&quot;(43, 154)(27, 177)&quot;</span>
</pre></div> </pre></div>
@ -494,7 +494,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
linux/simple_bash_function.html
View File

@ -208,7 +208,7 @@ The secret number is 126
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
linux/version_kernel.html
View File

@ -160,7 +160,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

8
machine-learning/LeastSquareRegressionLine.html
View File

@ -160,9 +160,9 @@ Where :</p>
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>a = 0.5999999999999996 <div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">=</span> <span class="mi">0</span><span class="p">.</span><span class="mi">5999999999999996</span>
b = 0.8000000000000002 <span class="n">b</span> <span class="o">=</span> <span class="mi">0</span><span class="p">.</span><span class="mi">8000000000000002</span>
Where Y=a+b*X <span class="k">Where</span> <span class="n">Y</span><span class="o">=</span><span class="n">a</span><span class="o">+</span><span class="n">b</span><span class="o">*</span><span class="n">X</span>
</pre></div> </pre></div>
@ -234,7 +234,7 @@ Where Y=a+b*X
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

4
machine-learning/Multiple_Linear_Regression.html
View File

@ -176,7 +176,7 @@ b_2\\
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Linear regression coefficients between Y and X : a=51.953488372092984, b_0=6.65116279069768, b_1=-11.162790697674419 <div class="highlight"><pre><span></span><span class="n">Linear</span> <span class="n">regression</span> <span class="n">coefficients</span> <span class="k">between</span> <span class="n">Y</span> <span class="k">and</span> <span class="n">X</span> <span class="p">:</span> <span class="n">a</span><span class="o">=</span><span class="mi">51</span><span class="p">.</span><span class="mi">953488372092984</span><span class="p">,</span> <span class="n">b_0</span><span class="o">=</span><span class="mi">6</span><span class="p">.</span><span class="mi">65116279069768</span><span class="p">,</span> <span class="n">b_1</span><span class="o">=-</span><span class="mi">11</span><span class="p">.</span><span class="mi">162790697674419</span>
</pre></div> </pre></div>
@ -248,7 +248,7 @@ b_2\\
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

888
machine-learning/Source code for the recommandation engine for articles.html
View File

@ -228,9 +228,9 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0 879 <div class="highlight"><pre><span></span><span class="mi">0</span> <span class="mi">879</span>
1 324 <span class="mi">1</span> <span class="mi">324</span>
Name: label, dtype: int64 <span class="n">Name</span><span class="p">:</span> <span class="n">label</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">int64</span>
</pre></div> </pre></div>
@ -395,10 +395,10 @@ Name: label, dtype: int64
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Accuracy = 80.6% <div class="highlight"><pre><span></span><span class="n">Accuracy</span> <span class="o">=</span> <span class="mi">80</span><span class="p">.</span><span class="mi">6</span><span class="o">%</span>
Confusion matrix, without normalization <span class="n">Confusion</span> <span class="n">matrix</span><span class="p">,</span> <span class="k">without</span> <span class="n">normalization</span>
[[624 35] <span class="p">[[</span><span class="mi">624</span> <span class="mi">35</span><span class="p">]</span>
[140 103]] <span class="p">[</span><span class="mi">140</span> <span class="mi">103</span><span class="p">]]</span>
</pre></div> </pre></div>
@ -459,7 +459,7 @@ Confusion matrix, without normalization
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>array([1], dtype=int64) <div class="highlight"><pre><span></span><span class="nb">array</span><span class="p">([</span><span class="mi">1</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">int64</span><span class="p">)</span>
</pre></div> </pre></div>
@ -493,42 +493,42 @@ Confusion matrix, without normalization
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>{&#39;classifier__C&#39;: 5.0, &#39;vectorizer__ngram_range&#39;: (1, 1), &#39;vectorizer__preprocessor&#39;: &lt;function mask_integers at 0x00000237491B67B8&gt;, &#39;vectorizer__stop_words&#39;: &#39;english&#39;} <div class="highlight"><pre><span></span>{<span class="s1">&#39;</span><span class="s">classifier__C</span><span class="s1">&#39;</span>: <span class="mi">5</span>.<span class="mi">0</span>, <span class="s1">&#39;</span><span class="s">vectorizer__ngram_range</span><span class="s1">&#39;</span>: <span class="ss">(</span><span class="mi">1</span>, <span class="mi">1</span><span class="ss">)</span>, <span class="s1">&#39;</span><span class="s">vectorizer__preprocessor</span><span class="s1">&#39;</span>: <span class="o">&lt;</span><span class="nv">function</span> <span class="nv">mask_integers</span> <span class="nv">at</span> <span class="mi">0</span><span class="nv">x00000237491B67B8</span><span class="o">&gt;</span>, <span class="s1">&#39;</span><span class="s">vectorizer__stop_words</span><span class="s1">&#39;</span>: <span class="s1">&#39;</span><span class="s">english</span><span class="s1">&#39;</span>}
0.711180124224 <span class="mi">0</span>.<span class="mi">711180124224</span>
Accuracy = 71.2% <span class="nv">Accuracy</span> <span class="o">=</span> <span class="mi">71</span>.<span class="mi">2</span><span class="o">%</span>
Confusion matrix, without normalization <span class="nv">Confusion</span> <span class="nv">matrix</span>, <span class="nv">without</span> <span class="nv">normalization</span>
[[153 0] [[<span class="mi">153</span> <span class="mi">0</span>]
[ 62 0]] [ <span class="mi">62</span> <span class="mi">0</span>]]
--------------------------------------------------------------------------- <span class="o">---------------------------------------------------------------------------</span>
ValueError Traceback (most recent call last) <span class="nv">ValueError</span> <span class="nv">Traceback</span> <span class="ss">(</span><span class="nv">most</span> <span class="nv">recent</span> <span class="k">call</span> <span class="nl">last</span><span class="ss">)</span>
&lt;ipython-input-9-3e0781e307fb&gt; in &lt;module&gt;() <span class="o">&lt;</span><span class="nv">ipython</span><span class="o">-</span><span class="nv">input</span><span class="o">-</span><span class="mi">9</span><span class="o">-</span><span class="mi">3</span><span class="nv">e0781e307fb</span><span class="o">&gt;</span> <span class="nv">in</span> <span class="o">&lt;</span><span class="nv">module</span><span class="o">&gt;</span><span class="ss">()</span>
25 pipeline_performance(testing.label, predicted_labels) <span class="mi">25</span> <span class="nv">pipeline_performance</span><span class="ss">(</span><span class="nv">testing</span>.<span class="nv">label</span>, <span class="nv">predicted_labels</span><span class="ss">)</span>
26 <span class="mi">26</span>
---&gt; 27 print_top_features(pipeline1, n_features=10) <span class="o">---&gt;</span> <span class="mi">27</span> <span class="nv">print_top_features</span><span class="ss">(</span><span class="nv">pipeline1</span>, <span class="nv">n_features</span><span class="o">=</span><span class="mi">10</span><span class="ss">)</span>
C:\Users\Guillaume\Documents\Code\recommandation\utils\plotting.py in print_top_features(pipeline, vectorizer_name, classifier_name, n_features) <span class="nv">C</span>:\<span class="nv">Users</span>\<span class="nv">Guillaume</span>\<span class="nv">Documents</span>\<span class="nv">Code</span>\<span class="nv">recommandation</span>\<span class="nv">utils</span>\<span class="nv">plotting</span>.<span class="nv">py</span> <span class="nv">in</span> <span class="nv">print_top_features</span><span class="ss">(</span><span class="nv">pipeline</span>, <span class="nv">vectorizer_name</span>, <span class="nv">classifier_name</span>, <span class="nv">n_features</span><span class="ss">)</span>
81 def print_top_features(pipeline, vectorizer_name=&#39;vectorizer&#39;, classifier_name=&#39;classifier&#39;, n_features=7): <span class="mi">81</span> <span class="nv">def</span> <span class="nv">print_top_features</span><span class="ss">(</span><span class="nv">pipeline</span>, <span class="nv">vectorizer_name</span><span class="o">=</span><span class="s1">&#39;</span><span class="s">vectorizer</span><span class="s1">&#39;</span>, <span class="nv">classifier_name</span><span class="o">=</span><span class="s1">&#39;</span><span class="s">classifier</span><span class="s1">&#39;</span>, <span class="nv">n_features</span><span class="o">=</span><span class="mi">7</span><span class="ss">)</span>:
82 vocabulary = np.array(pipeline.named_steps[vectorizer_name].get_feature_names()) <span class="mi">82</span> <span class="nv">vocabulary</span> <span class="o">=</span> <span class="nv">np</span>.<span class="nv">array</span><span class="ss">(</span><span class="nv">pipeline</span>.<span class="nv">named_steps</span>[<span class="nv">vectorizer_name</span>].<span class="nv">get_feature_names</span><span class="ss">())</span>
---&gt; 83 coefs = pipeline.named_steps[classifier_name].coef_[0] <span class="o">---&gt;</span> <span class="mi">83</span> <span class="nv">coefs</span> <span class="o">=</span> <span class="nv">pipeline</span>.<span class="nv">named_steps</span>[<span class="nv">classifier_name</span>].<span class="nv">coef_</span>[<span class="mi">0</span>]
84 top_feature_idx = np.argsort(coefs) <span class="mi">84</span> <span class="nv">top_feature_idx</span> <span class="o">=</span> <span class="nv">np</span>.<span class="nv">argsort</span><span class="ss">(</span><span class="nv">coefs</span><span class="ss">)</span>
85 top_features = vocabulary[top_feature_idx] <span class="mi">85</span> <span class="nv">top_features</span> <span class="o">=</span> <span class="nv">vocabulary</span>[<span class="nv">top_feature_idx</span>]
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\svm\base.py in coef_(self) <span class="nv">C</span>:\<span class="nv">Users</span>\<span class="nv">Guillaume</span>\<span class="nv">Anaconda3</span>\<span class="nv">lib</span>\<span class="nv">site</span><span class="o">-</span><span class="nv">packages</span>\<span class="nv">sklearn</span>\<span class="nv">svm</span>\<span class="nv">base</span>.<span class="nv">py</span> <span class="nv">in</span> <span class="nv">coef_</span><span class="ss">(</span><span class="nv">self</span><span class="ss">)</span>
483 def coef_(self): <span class="mi">483</span> <span class="nv">def</span> <span class="nv">coef_</span><span class="ss">(</span><span class="nv">self</span><span class="ss">)</span>:
484 if self.kernel != &#39;linear&#39;: <span class="mi">484</span> <span class="k">if</span> <span class="nv">self</span>.<span class="nv">kernel</span> <span class="o">!=</span> <span class="s1">&#39;</span><span class="s">linear</span><span class="s1">&#39;</span>:
--&gt; 485 raise ValueError(&#39;coef_ is only available when using a &#39; <span class="o">--&gt;</span> <span class="mi">485</span> <span class="nv">raise</span> <span class="nv">ValueError</span><span class="ss">(</span><span class="s1">&#39;</span><span class="s">coef_ is only available when using a </span><span class="s1">&#39;</span>
486 &#39;linear kernel&#39;) <span class="mi">486</span> <span class="s1">&#39;</span><span class="s">linear kernel</span><span class="s1">&#39;</span><span class="ss">)</span>
487 <span class="mi">487</span>
ValueError: coef_ is only available when using a linear kernel <span class="nv">ValueError</span>: <span class="nv">coef_</span> <span class="nv">is</span> <span class="nv">only</span> <span class="nv">available</span> <span class="nv">when</span> <span class="nv">using</span> <span class="nv">a</span> <span class="nv">linear</span> <span class="nv">kernel</span>
</pre></div> </pre></div>
@ -565,261 +565,261 @@ ValueError: coef_ is only available when using a linear kernel
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <div class="highlight"><pre><span></span><span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">820</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
neg_prob = np.log(1 - np.exp(self.feature_log_prob_)) <span class="n">neg_prob</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">np</span><span class="p">.</span><span class="n">exp</span><span class="p">(</span><span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span><span class="p">))</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">823</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">invalid</span> <span class="n">value</span> <span class="n">encountered</span> <span class="k">in</span> <span class="k">add</span>
jll += self.class_log_prior_ + neg_prob.sum(axis=1) <span class="n">jll</span> <span class="o">+=</span> <span class="k">self</span><span class="p">.</span><span class="n">class_log_prior_</span> <span class="o">+</span> <span class="n">neg_prob</span><span class="p">.</span><span class="k">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">801</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
{&#39;classifier__alpha&#39;: 0.25, &#39;classifier__fit_prior&#39;: True, &#39;vectorizer__ngram_range&#39;: (1, 1), &#39;vectorizer__preprocessor&#39;: &lt;function mask_integers at 0x00000237491B67B8&gt;, &#39;vectorizer__stop_words&#39;: &#39;english&#39;} <span class="err">{</span><span class="s1">&#39;classifier__alpha&#39;</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">25</span><span class="p">,</span> <span class="s1">&#39;classifier__fit_prior&#39;</span><span class="p">:</span> <span class="k">True</span><span class="p">,</span> <span class="s1">&#39;vectorizer__ngram_range&#39;</span><span class="p">:</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="s1">&#39;vectorizer__preprocessor&#39;</span><span class="p">:</span> <span class="o">&lt;</span><span class="k">function</span> <span class="n">mask_integers</span> <span class="k">at</span> <span class="mi">0</span><span class="n">x00000237491B67B8</span><span class="o">&gt;</span><span class="p">,</span> <span class="s1">&#39;vectorizer__stop_words&#39;</span><span class="p">:</span> <span class="s1">&#39;english&#39;</span><span class="err">}</span>
0.805900621118 <span class="mi">0</span><span class="p">.</span><span class="mi">805900621118</span>
Accuracy = 78.1% <span class="n">Accuracy</span> <span class="o">=</span> <span class="mi">78</span><span class="p">.</span><span class="mi">1</span><span class="o">%</span>
Confusion matrix, without normalization <span class="n">Confusion</span> <span class="n">matrix</span><span class="p">,</span> <span class="k">without</span> <span class="n">normalization</span>
[[140 13] <span class="p">[[</span><span class="mi">140</span> <span class="mi">13</span><span class="p">]</span>
[ 34 28]] <span class="p">[</span> <span class="mi">34</span> <span class="mi">28</span><span class="p">]]</span>
Top like features: <span class="n">Top</span> <span class="k">like</span> <span class="n">features</span><span class="p">:</span>
[&#39;use&#39; &#39;just&#39; &#39;year&#39; &#39;price&#39; &#39;time&#39; &#39;Bitcoin&#39; &#39;bitcoin&#39; &#39;new&#39; &#39;The&#39; <span class="p">[</span><span class="s1">&#39;use&#39;</span> <span class="s1">&#39;just&#39;</span> <span class="s1">&#39;year&#39;</span> <span class="s1">&#39;price&#39;</span> <span class="s1">&#39;time&#39;</span> <span class="s1">&#39;Bitcoin&#39;</span> <span class="s1">&#39;bitcoin&#39;</span> <span class="s1">&#39;new&#39;</span> <span class="s1">&#39;The&#39;</span>
&#39;INTMASK&#39;] <span class="s1">&#39;INTMASK&#39;</span><span class="p">]</span>
--- <span class="c1">---</span>
Top dislike features: <span class="n">Top</span> <span class="n">dislike</span> <span class="n">features</span><span class="p">:</span>
[&#39;ABBA&#39; &#39;cable&#39; &#39;cab&#39; &#39;byte&#39; &#39;publication&#39; &#39;bye&#39; &#39;publications&#39; &#39;publicity&#39; <span class="p">[</span><span class="s1">&#39;ABBA&#39;</span> <span class="s1">&#39;cable&#39;</span> <span class="s1">&#39;cab&#39;</span> <span class="s1">&#39;byte&#39;</span> <span class="s1">&#39;publication&#39;</span> <span class="s1">&#39;bye&#39;</span> <span class="s1">&#39;publications&#39;</span> <span class="s1">&#39;publicity&#39;</span>
&#39;buyer&#39; &#39;publicizing&#39;] <span class="s1">&#39;buyer&#39;</span> <span class="s1">&#39;publicizing&#39;</span><span class="p">]</span>
</pre></div> </pre></div>
@ -856,165 +856,165 @@ Top dislike features:
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <div class="highlight"><pre><span></span><span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log <span class="k">C</span><span class="p">:</span><span class="err">\</span><span class="n">Users</span><span class="err">\</span><span class="n">Guillaume</span><span class="err">\</span><span class="n">Anaconda3</span><span class="err">\</span><span class="n">lib</span><span class="err">\</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="err">\</span><span class="n">sklearn</span><span class="err">\</span><span class="n">naive_bayes</span><span class="p">.</span><span class="n">py</span><span class="p">:</span><span class="mi">699</span><span class="p">:</span> <span class="n">RuntimeWarning</span><span class="p">:</span> <span class="n">divide</span> <span class="k">by</span> <span class="n">zero</span> <span class="n">encountered</span> <span class="k">in</span> <span class="n">log</span>
self.feature_log_prob_ = (np.log(smoothed_fc) - <span class="k">self</span><span class="p">.</span><span class="n">feature_log_prob_</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="p">.</span><span class="n">log</span><span class="p">(</span><span class="n">smoothed_fc</span><span class="p">)</span> <span class="o">-</span>
{&#39;classifier__alpha&#39;: 0.5, &#39;classifier__fit_prior&#39;: False, &#39;vectorizer__ngram_range&#39;: (1, 1), &#39;vectorizer__preprocessor&#39;: &lt;function mask_integers at 0x00000237491B67B8&gt;, &#39;vectorizer__stop_words&#39;: &#39;english&#39;} <span class="err">{</span><span class="s1">&#39;classifier__alpha&#39;</span><span class="p">:</span> <span class="mi">0</span><span class="p">.</span><span class="mi">5</span><span class="p">,</span> <span class="s1">&#39;classifier__fit_prior&#39;</span><span class="p">:</span> <span class="k">False</span><span class="p">,</span> <span class="s1">&#39;vectorizer__ngram_range&#39;</span><span class="p">:</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="s1">&#39;vectorizer__preprocessor&#39;</span><span class="p">:</span> <span class="o">&lt;</span><span class="k">function</span> <span class="n">mask_integers</span> <span class="k">at</span> <span class="mi">0</span><span class="n">x00000237491B67B8</span><span class="o">&gt;</span><span class="p">,</span> <span class="s1">&#39;vectorizer__stop_words&#39;</span><span class="p">:</span> <span class="s1">&#39;english&#39;</span><span class="err">}</span>
0.80900621118 <span class="mi">0</span><span class="p">.</span><span class="mi">80900621118</span>
Accuracy = 79.1% <span class="n">Accuracy</span> <span class="o">=</span> <span class="mi">79</span><span class="p">.</span><span class="mi">1</span><span class="o">%</span>
Confusion matrix, without normalization <span class="n">Confusion</span> <span class="n">matrix</span><span class="p">,</span> <span class="k">without</span> <span class="n">normalization</span>
[[141 12] <span class="p">[[</span><span class="mi">141</span> <span class="mi">12</span><span class="p">]</span>
[ 33 29]] <span class="p">[</span> <span class="mi">33</span> <span class="mi">29</span><span class="p">]]</span>
Top like features: <span class="n">Top</span> <span class="k">like</span> <span class="n">features</span><span class="p">:</span>
[&#39;time&#39; &#39;Google&#39; &#39;Pro&#39; &#39;Apple&#39; &#39;new&#39; &#39;The&#39; &#39;Bitcoin&#39; &#39;price&#39; &#39;bitcoin&#39; <span class="p">[</span><span class="s1">&#39;time&#39;</span> <span class="s1">&#39;Google&#39;</span> <span class="s1">&#39;Pro&#39;</span> <span class="s1">&#39;Apple&#39;</span> <span class="s1">&#39;new&#39;</span> <span class="s1">&#39;The&#39;</span> <span class="s1">&#39;Bitcoin&#39;</span> <span class="s1">&#39;price&#39;</span> <span class="s1">&#39;bitcoin&#39;</span>
&#39;INTMASK&#39;] <span class="s1">&#39;INTMASK&#39;</span><span class="p">]</span>
--- <span class="c1">---</span>
Top dislike features: <span class="n">Top</span> <span class="n">dislike</span> <span class="n">features</span><span class="p">:</span>
[&#39;ABBA&#39; &#39;categories&#39; &#39;catching&#39; &#39;catalyst&#39; &#39;catalog&#39; &#39;casually&#39; &#39;casts&#39; <span class="p">[</span><span class="s1">&#39;ABBA&#39;</span> <span class="s1">&#39;categories&#39;</span> <span class="s1">&#39;catching&#39;</span> <span class="s1">&#39;catalyst&#39;</span> <span class="s1">&#39;catalog&#39;</span> <span class="s1">&#39;casually&#39;</span> <span class="s1">&#39;casts&#39;</span>
&#39;cast&#39; &#39;cashier&#39; &#39;ran&#39;] <span class="s1">&#39;cast&#39;</span> <span class="s1">&#39;cashier&#39;</span> <span class="s1">&#39;ran&#39;</span><span class="p">]</span>
</pre></div> </pre></div>
@ -1033,7 +1033,7 @@ Top dislike features:
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<center>This project contains 92 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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mathematics/Bayes.html
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@ -196,7 +196,7 @@
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mathematics/Binomial.html
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@ -256,7 +256,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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mathematics/Geometric.html
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@ -233,7 +233,7 @@ So :
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mathematics/KLD.html
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@ -214,7 +214,7 @@
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<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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mathematics/Number_edges_Complete_graph.html
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@ -195,7 +195,7 @@
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<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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mathematics/Premutations_and_combinations.html
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@ -203,7 +203,7 @@
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<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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mathematics/cond_prob.html
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@ -197,7 +197,7 @@ and B are considered to be independent if event A has no effect on the probabili
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<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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mathematics/normal.html
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@ -221,7 +221,7 @@ where <span class="math">\(erf\)</span> is the error function:
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<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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mathematics/pearson.html
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@ -206,7 +206,7 @@
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mathematics/poisson.html
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@ -222,7 +222,7 @@
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@ -223,7 +223,7 @@ $$</div>
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@ -145,7 +145,7 @@
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10
python/Efficient_extraction_of_eigenvalues_from_a_list_of_tensors.html
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@ -222,10 +222,10 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>array([[ 1. , 1. , 1. ], <div class="highlight"><pre><span></span><span class="nb">array</span><span class="p">([[</span> <span class="mi">1</span><span class="p">.</span> <span class="p">,</span> <span class="mi">1</span><span class="p">.</span> <span class="p">,</span> <span class="mi">1</span><span class="p">.</span> <span class="p">],</span>
[ 5.58442834, -0.80511809, -1.77931025], <span class="p">[</span> <span class="mi">5</span><span class="p">.</span><span class="mi">58442834</span><span class="p">,</span> <span class="o">-</span><span class="mi">0</span><span class="p">.</span><span class="mi">80511809</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">.</span><span class="mi">77931025</span><span class="p">],</span>
[-1.31577211, 8.85035616, 4.46541595], <span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">.</span><span class="mi">31577211</span><span class="p">,</span> <span class="mi">8</span><span class="p">.</span><span class="mi">85035616</span><span class="p">,</span> <span class="mi">4</span><span class="p">.</span><span class="mi">46541595</span><span class="p">],</span>
[ 1. , 2. , 3. ]]) <span class="p">[</span> <span class="mi">1</span><span class="p">.</span> <span class="p">,</span> <span class="mi">2</span><span class="p">.</span> <span class="p">,</span> <span class="mi">3</span><span class="p">.</span> <span class="p">]])</span>
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@ -152,7 +152,7 @@ conda install numpy --channel intel --override-channels
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>1.06 ms ± 91.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) <div class="highlight"><pre><span></span><span class="mi">1</span>.<span class="mi">06</span> <span class="nv">ms</span> ± <span class="mi">91</span>.<span class="mi">5</span> µ<span class="nv">s</span> <span class="nv">per</span> <span class="k">loop</span> <span class="ss">(</span><span class="nv">mean</span> ± <span class="nv">std</span>. <span class="nv">dev</span>. <span class="nv">of</span> <span class="mi">7</span> <span class="nv">runs</span>, <span class="mi">1000</span> <span class="nv">loops</span> <span class="nv">each</span><span class="ss">)</span>
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@ -160,7 +160,7 @@ conda install numpy --channel intel --override-channels
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>225 µs ± 3.46 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) <div class="highlight"><pre><span></span><span class="mi">225</span> µ<span class="nv">s</span> ± <span class="mi">3</span>.<span class="mi">46</span> µ<span class="nv">s</span> <span class="nv">per</span> <span class="k">loop</span> <span class="ss">(</span><span class="nv">mean</span> ± <span class="nv">std</span>. <span class="nv">dev</span>. <span class="nv">of</span> <span class="mi">7</span> <span class="nv">runs</span>, <span class="mi">1000</span> <span class="nv">loops</span> <span class="nv">each</span><span class="ss">)</span>
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Get items in one dictionnary but not the other one
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<p>Say we have two similar dictonnaries, we want to find all the items that are in the second dictonnary but not in the first one.</p>
<div class="highlight"><pre><span></span><span class="n">dict1</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;Banana&quot;</span><span class="p">:</span> <span class="s2">&quot;yellow&quot;</span><span class="p">,</span> <span class="s2">&quot;Orange&quot;</span><span class="p">:</span> <span class="s2">&quot;orange&quot;</span><span class="p">}</span>
<span class="n">dict2</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;Banana&quot;</span><span class="p">:</span> <span class="s2">&quot;yellow&quot;</span><span class="p">,</span> <span class="s2">&quot;Orange&quot;</span><span class="p">:</span> <span class="s2">&quot;orange&quot;</span><span class="p">,</span> <span class="s2">&quot;Lemon&quot;</span><span class="p">:</span><span class="s2">&quot;yellow&quot;</span><span class="p">}</span>
</pre></div>
<p>In the following code we find the difference of the keys and then rebuild a dict taking the corresponding values.</p>
<div class="highlight"><pre><span></span><span class="n">difference</span> <span class="o">=</span> <span class="p">{</span> <span class="n">k</span> <span class="p">:</span> <span class="n">dict2</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">dict2</span><span class="p">)</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">dict1</span><span class="p">)</span> <span class="p">}</span>
<span class="n">difference</span>
</pre></div>
<div class="highlight"><pre><span></span><span class="err">{</span><span class="s1">&#39;Lemon&#39;</span><span class="p">:</span> <span class="s1">&#39;yellow&#39;</span><span class="err">}</span>
</pre></div>
<p>Be careful, this operation is not symetric. This means that if we want to find a value present in dict1 but not in dict2 this code won't work</p>
<div class="highlight"><pre><span></span><span class="n">dict1</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;Banana&quot;</span><span class="p">:</span> <span class="s2">&quot;yellow&quot;</span><span class="p">,</span> <span class="s2">&quot;Orange&quot;</span><span class="p">:</span> <span class="s2">&quot;orange&quot;</span><span class="p">,</span> <span class="s2">&quot;Lemon&quot;</span><span class="p">:</span><span class="s2">&quot;yellow&quot;</span><span class="p">}</span>
<span class="n">dict2</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;Banana&quot;</span><span class="p">:</span> <span class="s2">&quot;yellow&quot;</span><span class="p">,</span> <span class="s2">&quot;Orange&quot;</span><span class="p">:</span> <span class="s2">&quot;orange&quot;</span><span class="p">}</span>
<span class="n">difference</span> <span class="o">=</span> <span class="p">{</span> <span class="n">k</span> <span class="p">:</span> <span class="n">dict2</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">set</span><span class="p">(</span><span class="n">dict2</span><span class="p">)</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">dict1</span><span class="p">)</span> <span class="p">}</span>
<span class="n">difference</span>
</pre></div>
<div class="highlight"><pre><span></span><span class="err">{}</span>
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@ -152,8 +152,8 @@ myvariable: 42
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>hello world <div class="highlight"><pre><span></span><span class="n">hello</span> <span class="n">world</span>
42 <span class="mi">42</span>
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@ -169,7 +169,7 @@ myvariable: 42
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<div class="highlight"><pre><span></span>Array : [1, 2, 3, 3, 4, 5, 3, 6, 7, 7] <div class="highlight"><pre><span></span><span class="nb">Array</span> <span class="p">:</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">7</span><span class="p">]</span>
The number 3 appears 3 times in the list <span class="n">The</span> <span class="nb">number</span> <span class="mi">3</span> <span class="n">appears</span> <span class="mi">3</span> <span class="n">times</span> <span class="k">in</span> <span class="n">the</span> <span class="n">list</span>
The number 7 appears 2 times in the list <span class="n">The</span> <span class="nb">number</span> <span class="mi">7</span> <span class="n">appears</span> <span class="mi">2</span> <span class="n">times</span> <span class="k">in</span> <span class="n">the</span> <span class="n">list</span>
The number 4 appears 1 times in the list <span class="n">The</span> <span class="nb">number</span> <span class="mi">4</span> <span class="n">appears</span> <span class="mi">1</span> <span class="n">times</span> <span class="k">in</span> <span class="n">the</span> <span class="n">list</span>
</pre></div> </pre></div>
@ -152,7 +152,7 @@ The number 4 appears 1 times in the list
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Counter({1: 1, 2: 1, 3: 3, 4: 1, 5: 1, 6: 1, 7: 2}) <div class="highlight"><pre><span></span><span class="n">Counter</span><span class="p">(</span><span class="err">{</span><span class="mi">1</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">:</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">5</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">6</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">7</span><span class="p">:</span> <span class="mi">2</span><span class="err">}</span><span class="p">)</span>
</pre></div> </pre></div>
@ -165,7 +165,7 @@ The number 4 appears 1 times in the list
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>{1: 1, 2: 1, 3: 3, 4: 1, 5: 1, 6: 1, 7: 2} <div class="highlight"><pre><span></span><span class="err">{</span><span class="mi">1</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">:</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">5</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">6</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">7</span><span class="p">:</span> <span class="mi">2</span><span class="err">}</span>
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@ -181,7 +181,7 @@ The number 4 appears 1 times in the list
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<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

6
python/dask_infiniband.html
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@ -127,12 +127,12 @@
<div class='article_content'> <div class='article_content'>
<p>InfiniBand (abbreviated IB) is a computer-networking communications standard used in high-performance computing that features very high throughput and very low latency. It is used for data interconnect both among and within computers. InfiniBand is also used as either a direct or switched interconnect between servers and storage systems, as well as an interconnect between storage systems. (source Wikipedia).</p> <p>InfiniBand (abbreviated IB) is a computer-networking communications standard used in high-performance computing that features very high throughput and very low latency. It is used for data interconnect both among and within computers. InfiniBand is also used as either a direct or switched interconnect between servers and storage systems, as well as an interconnect between storage systems. (source Wikipedia).</p>
<p>If you want to leverage this high speed network instead of the regular ethernet network, you have to specify to the scheduler that you want to used infiniband as your interface. Assuming that you Infiniband interface is <code>ib0</code>, you would call the scheduler like this :</p> <p>If you want to leverage this high speed network instead of the regular ethernet network, you have to specify to the scheduler that you want to used infiniband as your interface. Assuming that you Infiniband interface is <code>ib0</code>, you would call the scheduler like this :</p>
<div class="highlight"><pre><span></span>dask-scheduler --interface ib0 --scheduler-file ./cluster.yaml <div class="highlight"><pre><span></span><span class="n">dask</span><span class="o">-</span><span class="n">scheduler</span> <span class="c1">--interface ib0 --scheduler-file ./cluster.yaml</span>
</pre></div> </pre></div>
<p>you would have to call the worker using the same interface :</p> <p>you would have to call the worker using the same interface :</p>
<div class="highlight"><pre><span></span>dask-worker --interface ib0 --scheduler-file ./cluster.yaml <div class="highlight"><pre><span></span><span class="n">dask</span><span class="o">-</span><span class="n">worker</span> <span class="c1">--interface ib0 --scheduler-file ./cluster.yaml</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -148,7 +148,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

16
python/design_own_libs.html
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@ -182,13 +182,13 @@
<h2>Structure your repository</h2> <h2>Structure your repository</h2>
<p>You should have a file structure in your repository. It will help other contributers especially future contributers.</p> <p>You should have a file structure in your repository. It will help other contributers especially future contributers.</p>
<p>A nice directory structure for your project should look like this:</p> <p>A nice directory structure for your project should look like this:</p>
<div class="highlight"><pre><span></span>README.md <div class="highlight"><pre><span></span><span class="n">README</span><span class="p">.</span><span class="n">md</span>
LICENSE <span class="n">LICENSE</span>
setup.py <span class="n">setup</span><span class="p">.</span><span class="n">py</span>
requirements.txt <span class="n">requirements</span><span class="p">.</span><span class="n">txt</span>
./MyPackage <span class="p">.</span><span class="o">/</span><span class="n">MyPackage</span>
./docs <span class="p">.</span><span class="o">/</span><span class="n">docs</span>
./tests <span class="p">.</span><span class="o">/</span><span class="n">tests</span>
</pre></div> </pre></div>
@ -232,7 +232,7 @@ The list of dependencies required to test, build and generate the doc are listed
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

6
python/dict_comprehension.html
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@ -137,7 +137,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>{&#39;0&#39;: 0, &#39;1&#39;: 1, &#39;2&#39;: 4, &#39;3&#39;: 9, &#39;4&#39;: 16, &#39;5&#39;: 25, &#39;6&#39;: 36, &#39;7&#39;: 49, &#39;8&#39;: 64, &#39;9&#39;: 81} <div class="highlight"><pre><span></span><span class="err">{</span><span class="s1">&#39;0&#39;</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;1&#39;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;2&#39;</span><span class="p">:</span> <span class="mi">4</span><span class="p">,</span> <span class="s1">&#39;3&#39;</span><span class="p">:</span> <span class="mi">9</span><span class="p">,</span> <span class="s1">&#39;4&#39;</span><span class="p">:</span> <span class="mi">16</span><span class="p">,</span> <span class="s1">&#39;5&#39;</span><span class="p">:</span> <span class="mi">25</span><span class="p">,</span> <span class="s1">&#39;6&#39;</span><span class="p">:</span> <span class="mi">36</span><span class="p">,</span> <span class="s1">&#39;7&#39;</span><span class="p">:</span> <span class="mi">49</span><span class="p">,</span> <span class="s1">&#39;8&#39;</span><span class="p">:</span> <span class="mi">64</span><span class="p">,</span> <span class="s1">&#39;9&#39;</span><span class="p">:</span> <span class="mi">81</span><span class="err">}</span>
</pre></div> </pre></div>
@ -148,7 +148,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>{&#39;France&#39;: 67120000.0, &#39;UK&#39;: 66020000.0, &#39;USA&#39;: 325700000.0, &#39;China&#39;: 1386000000.0, &#39;Germany&#39;: 82790000.0} <div class="highlight"><pre><span></span><span class="err">{</span><span class="s1">&#39;France&#39;</span><span class="p">:</span> <span class="mi">67120000</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;UK&#39;</span><span class="p">:</span> <span class="mi">66020000</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;USA&#39;</span><span class="p">:</span> <span class="mi">325700000</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;China&#39;</span><span class="p">:</span> <span class="mi">1386000000</span><span class="p">.</span><span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;Germany&#39;</span><span class="p">:</span> <span class="mi">82790000</span><span class="p">.</span><span class="mi">0</span><span class="err">}</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -164,7 +164,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

6
python/ensure_dir.html
View File

@ -139,7 +139,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>False <div class="highlight"><pre><span></span><span class="k">False</span>
</pre></div> </pre></div>
@ -161,7 +161,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>True <div class="highlight"><pre><span></span><span class="k">True</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -177,7 +177,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

6
python/iterate_dict.html
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@ -34,7 +34,7 @@
<![endif]--> <![endif]-->
<meta name="tags" content="Other" /> <meta name="tags" content="Basics" />
</head> </head>
@ -121,7 +121,7 @@
</time> </time>
</li> </li>
<li>Python</li> <li>Python</li>
<li>Other</li> <li>Basics</li>
</ol> </ol>
</header> </header>
<div class='article_content'> <div class='article_content'>
@ -158,7 +158,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

28
python/list_files_directory.html
View File

@ -137,7 +137,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[&#39;logfile.log&#39;, &#39;myfile.txt&#39;, &#39;super_music.mp3&#39;, &#39;textfile.txt&#39;] <div class="highlight"><pre><span></span><span class="p">[</span><span class="s1">&#39;logfile.log&#39;</span><span class="p">,</span> <span class="s1">&#39;myfile.txt&#39;</span><span class="p">,</span> <span class="s1">&#39;super_music.mp3&#39;</span><span class="p">,</span> <span class="s1">&#39;textfile.txt&#39;</span><span class="p">]</span>
</pre></div> </pre></div>
@ -147,7 +147,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[&#39;myfile.txt&#39;, &#39;textfile.txt&#39;] <div class="highlight"><pre><span></span><span class="p">[</span><span class="s1">&#39;myfile.txt&#39;</span><span class="p">,</span> <span class="s1">&#39;textfile.txt&#39;</span><span class="p">]</span>
</pre></div> </pre></div>
@ -159,7 +159,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[&#39;myfile.txt&#39;] <div class="highlight"><pre><span></span><span class="p">[</span><span class="s1">&#39;myfile.txt&#39;</span><span class="p">]</span>
</pre></div> </pre></div>
@ -170,9 +170,9 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[&#39;./test_directory\\myfile.txt&#39;, <div class="highlight"><pre><span></span><span class="p">[</span><span class="s1">&#39;./test_directory\\myfile.txt&#39;</span><span class="p">,</span>
&#39;./test_directory\\textfile.txt&#39;, <span class="s1">&#39;./test_directory\\textfile.txt&#39;</span><span class="p">,</span>
&#39;./test_directory\\subdir1\\file_hidden_in_a_sub_direcotry.txt&#39;] <span class="s1">&#39;./test_directory\\subdir1\\file_hidden_in_a_sub_direcotry.txt&#39;</span><span class="p">]</span>
</pre></div> </pre></div>
@ -183,9 +183,9 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[WindowsPath(&#39;test_directory/myfile.txt&#39;), <div class="highlight"><pre><span></span><span class="p">[</span><span class="n">WindowsPath</span><span class="p">(</span><span class="s1">&#39;test_directory/myfile.txt&#39;</span><span class="p">),</span>
WindowsPath(&#39;test_directory/textfile.txt&#39;), <span class="n">WindowsPath</span><span class="p">(</span><span class="s1">&#39;test_directory/textfile.txt&#39;</span><span class="p">),</span>
WindowsPath(&#39;test_directory/subdir1/file_hidden_in_a_sub_direcotry.txt&#39;)] <span class="n">WindowsPath</span><span class="p">(</span><span class="s1">&#39;test_directory/subdir1/file_hidden_in_a_sub_direcotry.txt&#39;</span><span class="p">)]</span>
</pre></div> </pre></div>
@ -194,10 +194,10 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>[WindowsPath(&#39;test_directory/logfile.log&#39;), <div class="highlight"><pre><span></span><span class="p">[</span><span class="n">WindowsPath</span><span class="p">(</span><span class="s1">&#39;test_directory/logfile.log&#39;</span><span class="p">),</span>
WindowsPath(&#39;test_directory/myfile.txt&#39;), <span class="n">WindowsPath</span><span class="p">(</span><span class="s1">&#39;test_directory/myfile.txt&#39;</span><span class="p">),</span>
WindowsPath(&#39;test_directory/textfile.txt&#39;), <span class="n">WindowsPath</span><span class="p">(</span><span class="s1">&#39;test_directory/textfile.txt&#39;</span><span class="p">),</span>
WindowsPath(&#39;test_directory/subdir1/file_hidden_in_a_sub_direcotry.txt&#39;)] <span class="n">WindowsPath</span><span class="p">(</span><span class="s1">&#39;test_directory/subdir1/file_hidden_in_a_sub_direcotry.txt&#39;</span><span class="p">)]</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -213,7 +213,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

90
python/list_windows.html
View File

@ -10,7 +10,7 @@
<meta name="author" content="Guillaume Redoulès"> <meta name="author" content="Guillaume Redoulès">
<link rel="icon" href="../favicon.ico"> <link rel="icon" href="../favicon.ico">
<title>Liste all opened windows on Windows - Python</title> <title>List all opened windows on Windows - Python</title>
<!-- JQuery --> <!-- JQuery -->
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.3/jquery.min.js"></script> <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.3/jquery.min.js"></script>
@ -112,7 +112,7 @@
<section id="content" class="body"> <section id="content" class="body">
<header> <header>
<h1> <h1>
Liste all opened windows on Windows List all opened windows on Windows
</h1> </h1>
<ol class="breadcrumb"> <ol class="breadcrumb">
<li> <li>
@ -149,27 +149,27 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>{&#39;&#39;: 3802422, <div class="highlight"><pre><span></span><span class="err">{</span><span class="s1">&#39;&#39;</span><span class="p">:</span> <span class="mi">3802422</span><span class="p">,</span>
&#39;Forcepad driver tray window&#39;: 65676, <span class="s1">&#39;Forcepad driver tray window&#39;</span><span class="p">:</span> <span class="mi">65676</span><span class="p">,</span>
&#39;Jauge de batterie&#39;: 131542, <span class="s1">&#39;Jauge de batterie&#39;</span><span class="p">:</span> <span class="mi">131542</span><span class="p">,</span>
&#39;Network Flyout&#39;: 131650, <span class="s1">&#39;Network Flyout&#39;</span><span class="p">:</span> <span class="mi">131650</span><span class="p">,</span>
&#39;Dashlane&#39;: 5570658, <span class="s1">&#39;Dashlane&#39;</span><span class="p">:</span> <span class="mi">5570658</span><span class="p">,</span>
&#39;Wox&#39;: 131770, <span class="s1">&#39;Wox&#39;</span><span class="p">:</span> <span class="mi">131770</span><span class="p">,</span>
&#39;JupyterLab - Brave&#39;: 66990, <span class="s1">&#39;JupyterLab - Brave&#39;</span><span class="p">:</span> <span class="mi">66990</span><span class="p">,</span>
&#39;python&#39;: 4261478, <span class="s1">&#39;python&#39;</span><span class="p">:</span> <span class="mi">4261478</span><span class="p">,</span>
&#39;Visual Studio Code - Insiders&#39;: 329780, <span class="s1">&#39;Visual Studio Code - Insiders&#39;</span><span class="p">:</span> <span class="mi">329780</span><span class="p">,</span>
&#39;Code - Insiders&#39;: 526478, <span class="s1">&#39;Code - Insiders&#39;</span><span class="p">:</span> <span class="mi">526478</span><span class="p">,</span>
&#39;Documents&#39;: 526010, <span class="s1">&#39;Documents&#39;</span><span class="p">:</span> <span class="mi">526010</span><span class="p">,</span>
&#39;Windows PowerShell&#39;: 198580, <span class="s1">&#39;Windows PowerShell&#39;</span><span class="p">:</span> <span class="mi">198580</span><span class="p">,</span>
&#39;Progression&#39;: 394934, <span class="s1">&#39;Progression&#39;</span><span class="p">:</span> <span class="mi">394934</span><span class="p">,</span>
&#39;Microsoft Edge&#39;: 131586, <span class="s1">&#39;Microsoft Edge&#39;</span><span class="p">:</span> <span class="mi">131586</span><span class="p">,</span>
&#39;Microsoft Store&#39;: 197328, <span class="s1">&#39;Microsoft Store&#39;</span><span class="p">:</span> <span class="mi">197328</span><span class="p">,</span>
&#39;QTrayIconMessageWindow&#39;: 327816, <span class="s1">&#39;QTrayIconMessageWindow&#39;</span><span class="p">:</span> <span class="mi">327816</span><span class="p">,</span>
&#39;Hidden Window&#39;: 459506, <span class="s1">&#39;Hidden Window&#39;</span><span class="p">:</span> <span class="mi">459506</span><span class="p">,</span>
&#39;.NET-BroadcastEventWindow.4.0.0.0.3e2c690.0&#39;: 131824, <span class="s1">&#39;.NET-BroadcastEventWindow.4.0.0.0.3e2c690.0&#39;</span><span class="p">:</span> <span class="mi">131824</span><span class="p">,</span>
&#39;SystemResourceNotifyWindow&#39;: 197346, <span class="s1">&#39;SystemResourceNotifyWindow&#39;</span><span class="p">:</span> <span class="mi">197346</span><span class="p">,</span>
&#39;MediaContextNotificationWindow&#39;: 197344, <span class="s1">&#39;MediaContextNotificationWindow&#39;</span><span class="p">:</span> <span class="mi">197344</span><span class="p">,</span>
&#39;Resilio Sync 2.6.3&#39;: 262934, <span class="s1">&#39;Resilio Sync 2.6.3&#39;</span><span class="p">:</span> <span class="mi">262934</span><span class="p">,</span>
</pre></div> </pre></div>
@ -181,27 +181,27 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>List of all opened windows : <div class="highlight"><pre><span></span><span class="n">List</span> <span class="k">of</span> <span class="k">all</span> <span class="n">opened</span> <span class="n">windows</span> <span class="p">:</span>
* Forcepad driver tray window <span class="o">*</span> <span class="n">Forcepad</span> <span class="n">driver</span> <span class="n">tray</span> <span class="n">window</span>
* Jauge de batterie <span class="o">*</span> <span class="n">Jauge</span> <span class="n">de</span> <span class="n">batterie</span>
* Network Flyout <span class="o">*</span> <span class="n">Network</span> <span class="n">Flyout</span>
* Dashlane <span class="o">*</span> <span class="n">Dashlane</span>
* Wox <span class="o">*</span> <span class="n">Wox</span>
* JupyterLab - Brave <span class="o">*</span> <span class="n">JupyterLab</span> <span class="o">-</span> <span class="n">Brave</span>
* python <span class="o">*</span> <span class="n">python</span>
* Visual Studio Code - Insiders <span class="o">*</span> <span class="n">Visual</span> <span class="n">Studio</span> <span class="n">Code</span> <span class="o">-</span> <span class="n">Insiders</span>
* Code - Insiders <span class="o">*</span> <span class="n">Code</span> <span class="o">-</span> <span class="n">Insiders</span>
* Documents <span class="o">*</span> <span class="n">Documents</span>
* Windows PowerShell <span class="o">*</span> <span class="n">Windows</span> <span class="n">PowerShell</span>
* Progression <span class="o">*</span> <span class="n">Progression</span>
* Microsoft Edge <span class="o">*</span> <span class="n">Microsoft</span> <span class="n">Edge</span>
* Microsoft Store <span class="o">*</span> <span class="n">Microsoft</span> <span class="n">Store</span>
* QTrayIconMessageWindow <span class="o">*</span> <span class="n">QTrayIconMessageWindow</span>
* Hidden Window <span class="o">*</span> <span class="n">Hidden</span> <span class="n">Window</span>
* .NET-BroadcastEventWindow.4.0.0.0.3e2c690.0 <span class="o">*</span> <span class="p">.</span><span class="n">NET</span><span class="o">-</span><span class="n">BroadcastEventWindow</span><span class="p">.</span><span class="mi">4</span><span class="p">.</span><span class="mi">0</span><span class="p">.</span><span class="mi">0</span><span class="p">.</span><span class="mi">0</span><span class="p">.</span><span class="mi">3</span><span class="n">e2c690</span><span class="p">.</span><span class="mi">0</span>
* SystemResourceNotifyWindow <span class="o">*</span> <span class="n">SystemResourceNotifyWindow</span>
* MediaContextNotificationWindow <span class="o">*</span> <span class="n">MediaContextNotificationWindow</span>
* Resilio Sync 2.6.3 <span class="o">*</span> <span class="n">Resilio</span> <span class="n">Sync</span> <span class="mi">2</span><span class="p">.</span><span class="mi">6</span><span class="p">.</span><span class="mi">3</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -217,7 +217,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

10
python/maximize_window.html
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@ -141,7 +141,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>24 <div class="highlight"><pre><span></span><span class="mi">24</span>
</pre></div> </pre></div>
@ -150,7 +150,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>24 <div class="highlight"><pre><span></span><span class="mi">24</span>
</pre></div> </pre></div>
@ -159,7 +159,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>24 <div class="highlight"><pre><span></span><span class="mi">24</span>
</pre></div> </pre></div>
@ -172,7 +172,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0 <div class="highlight"><pre><span></span><span class="mi">0</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -188,7 +188,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

18
python/pandas_extended_types.html
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@ -145,14 +145,14 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>0 1.0 <div class="highlight"><pre><span></span><span class="mi">0</span> <span class="mi">1</span><span class="p">.</span><span class="mi">0</span>
1 NaN <span class="mi">1</span> <span class="n">NaN</span>
2 2.0 <span class="mi">2</span> <span class="mi">2</span><span class="p">.</span><span class="mi">0</span>
dtype: float64 <span class="n">dtype</span><span class="p">:</span> <span class="n">float64</span>
0 1.0 <span class="mi">0</span> <span class="mi">1</span><span class="p">.</span><span class="mi">0</span>
1 NaN <span class="mi">1</span> <span class="n">NaN</span>
2 2.0 <span class="mi">2</span> <span class="mi">2</span><span class="p">.</span><span class="mi">0</span>
dtype: Int64 <span class="n">dtype</span><span class="p">:</span> <span class="n">Int64</span>
</pre></div> </pre></div>
@ -181,7 +181,7 @@ dtype: Int64
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
python/quandl.html
View File

@ -237,7 +237,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

4
python/randint.html
View File

@ -140,7 +140,7 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>My pseudo random number between 126 and 211 : 206 <div class="highlight"><pre><span></span><span class="nv">My</span> <span class="nv">pseudo</span> <span class="k">random</span> <span class="nv">number</span> <span class="nv">between</span> <span class="mi">126</span> <span class="nv">and</span> <span class="mi">211</span> : <span class="mi">206</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -156,7 +156,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
python/rename_columns_pandas.html
View File

@ -647,7 +647,7 @@ you also need to specify the axis.</p>
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

10
python/reverse.html
View File

@ -137,9 +137,9 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Initial array : [0, 1, 2, 3, 4] <div class="highlight"><pre><span></span><span class="n">Initial</span> <span class="nb">array</span> <span class="p">:</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]</span>
Reversed array : [4, 3, 2, 1, 0] <span class="n">Reversed</span> <span class="nb">array</span> <span class="p">:</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span>
</pre></div> </pre></div>
@ -155,9 +155,9 @@ Reversed array : [4, 3, 2, 1, 0]
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Initial array : [0 1 2 3 4] <div class="highlight"><pre><span></span><span class="n">Initial</span> <span class="nb">array</span> <span class="p">:</span> <span class="p">[</span><span class="mi">0</span> <span class="mi">1</span> <span class="mi">2</span> <span class="mi">3</span> <span class="mi">4</span><span class="p">]</span>
Reversed array : [4 3 2 1 0] <span class="n">Reversed</span> <span class="nb">array</span> <span class="p">:</span> <span class="p">[</span><span class="mi">4</span> <span class="mi">3</span> <span class="mi">2</span> <span class="mi">1</span> <span class="mi">0</span><span class="p">]</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -173,7 +173,7 @@ Reversed array : [4 3 2 1 0]
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
python/reverse_column_order.html
View File

@ -288,7 +288,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
python/reverse_row_order.html
View File

@ -359,7 +359,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

14
python/sorting.html
View File

@ -140,9 +140,9 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Initial random list : [277, 347, 976, 367, 604, 878, 148, 670, 229, 432] <div class="highlight"><pre><span></span><span class="nv">Initial</span> <span class="k">random</span> <span class="nv">list</span> : [<span class="mi">277</span>, <span class="mi">347</span>, <span class="mi">976</span>, <span class="mi">367</span>, <span class="mi">604</span>, <span class="mi">878</span>, <span class="mi">148</span>, <span class="mi">670</span>, <span class="mi">229</span>, <span class="mi">432</span>]
Sorted list : [148, 229, 277, 347, 367, 432, 604, 670, 878, 976] <span class="nv">Sorted</span> <span class="nv">list</span> : [<span class="mi">148</span>, <span class="mi">229</span>, <span class="mi">277</span>, <span class="mi">347</span>, <span class="mi">367</span>, <span class="mi">432</span>, <span class="mi">604</span>, <span class="mi">670</span>, <span class="mi">878</span>, <span class="mi">976</span>]
</pre></div> </pre></div>
@ -156,9 +156,9 @@ Sorted list : [148, 229, 277, 347, 367, 432, 604, 670, 878, 976]
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Initial random list : [727, 759, 68, 103, 23, 90, 258, 737, 791, 567] <div class="highlight"><pre><span></span><span class="nv">Initial</span> <span class="k">random</span> <span class="nv">list</span> : [<span class="mi">727</span>, <span class="mi">759</span>, <span class="mi">68</span>, <span class="mi">103</span>, <span class="mi">23</span>, <span class="mi">90</span>, <span class="mi">258</span>, <span class="mi">737</span>, <span class="mi">791</span>, <span class="mi">567</span>]
Sorted list : [23, 68, 90, 103, 258, 567, 727, 737, 759, 791] <span class="nv">Sorted</span> <span class="nv">list</span> : [<span class="mi">23</span>, <span class="mi">68</span>, <span class="mi">90</span>, <span class="mi">103</span>, <span class="mi">258</span>, <span class="mi">567</span>, <span class="mi">727</span>, <span class="mi">737</span>, <span class="mi">759</span>, <span class="mi">791</span>]
</pre></div> </pre></div>
@ -174,9 +174,9 @@ Sorted list : [23, 68, 90, 103, 258, 567, 727, 737, 759, 791]
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Initial random array : [0.40021786 0.13876208 0.19939047 0.46015169 0.43734158] <div class="highlight"><pre><span></span><span class="nv">Initial</span> <span class="k">random</span> <span class="nv">array</span> : [<span class="mi">0</span>.<span class="mi">40021786</span> <span class="mi">0</span>.<span class="mi">13876208</span> <span class="mi">0</span>.<span class="mi">19939047</span> <span class="mi">0</span>.<span class="mi">46015169</span> <span class="mi">0</span>.<span class="mi">43734158</span>]
Sorted array : [0.13876208 0.19939047 0.40021786 0.43734158 0.46015169] <span class="nv">Sorted</span> <span class="nv">array</span> : [<span class="mi">0</span>.<span class="mi">13876208</span> <span class="mi">0</span>.<span class="mi">19939047</span> <span class="mi">0</span>.<span class="mi">40021786</span> <span class="mi">0</span>.<span class="mi">43734158</span> <span class="mi">0</span>.<span class="mi">46015169</span>]
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -192,7 +192,7 @@ Sorted array : [0.13876208 0.19939047 0.40021786 0.43734158 0.46015169]
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

10
python/unique.html
View File

@ -136,8 +136,8 @@
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Original List : [10, 20, 30, 40, 20, 50, 60, 40] <div class="highlight"><pre><span></span><span class="n">Original</span> <span class="n">List</span> <span class="p">:</span> <span class="p">[</span><span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mi">40</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">60</span><span class="p">,</span> <span class="mi">40</span><span class="p">]</span>
List of unique numbers : [40, 10, 50, 20, 60, 30] <span class="n">List</span> <span class="k">of</span> <span class="k">unique</span> <span class="n">numbers</span> <span class="p">:</span> <span class="p">[</span><span class="mi">40</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">50</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">60</span><span class="p">,</span> <span class="mi">30</span><span class="p">]</span>
</pre></div> </pre></div>
@ -153,9 +153,9 @@ List of unique numbers : [40, 10, 50, 20, 60, 30]
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>Initial numpy array : [10 20 30 40 20 50 60 40] <div class="highlight"><pre><span></span><span class="n">Initial</span> <span class="n">numpy</span> <span class="nb">array</span> <span class="p">:</span> <span class="p">[</span><span class="mi">10</span> <span class="mi">20</span> <span class="mi">30</span> <span class="mi">40</span> <span class="mi">20</span> <span class="mi">50</span> <span class="mi">60</span> <span class="mi">40</span><span class="p">]</span>
Numpy array with unique values : [10 20 30 40 50 60] <span class="n">Numpy</span> <span class="nb">array</span> <span class="k">with</span> <span class="k">unique</span> <span class="k">values</span> <span class="p">:</span> <span class="p">[</span><span class="mi">10</span> <span class="mi">20</span> <span class="mi">30</span> <span class="mi">40</span> <span class="mi">50</span> <span class="mi">60</span><span class="p">]</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -171,7 +171,7 @@ Numpy array with unique values : [10 20 30 40 50 60]
<footer class="footer"> <footer class="footer">
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<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
python/write_config_file.html
View File

@ -176,7 +176,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
search.html
View File

@ -112,7 +112,7 @@
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 92 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

16
sitemap.xml
View File

@ -5,7 +5,7 @@ xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
<url> <url>
<loc>redoules.github.io/</loc> <loc>redoules.github.io/</loc>
<lastmod>2019-08-14T21:39:48-00:00</lastmod> <lastmod>2019-08-22T20:57:14-00:00</lastmod>
<changefreq>daily</changefreq> <changefreq>daily</changefreq>
<priority>0.5</priority> <priority>0.5</priority>
</url> </url>
@ -17,6 +17,13 @@ xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
<priority>0.5</priority> <priority>0.5</priority>
</url> </url>
<url>
<loc>redoules.github.io/python/compare_dict.html</loc>
<lastmod>2019-08-22T14:12:00+02:00</lastmod>
<changefreq>monthly</changefreq>
<priority>0.5</priority>
</url>
<url> <url>
<loc>redoules.github.io/python/maximize_window.html</loc> <loc>redoules.github.io/python/maximize_window.html</loc>
<lastmod>2019-08-12T11:31:00+02:00</lastmod> <lastmod>2019-08-12T11:31:00+02:00</lastmod>
@ -52,6 +59,13 @@ xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
<priority>0.5</priority> <priority>0.5</priority>
</url> </url>
<url>
<loc>redoules.github.io/python/list_windows.html</loc>
<lastmod>2019-08-03T11:36:00+02:00</lastmod>
<changefreq>monthly</changefreq>
<priority>0.5</priority>
</url>
<url> <url>
<loc>redoules.github.io/python/reverse_column_order.html</loc> <loc>redoules.github.io/python/reverse_column_order.html</loc>
<lastmod>2019-08-03T08:45:00+02:00</lastmod> <lastmod>2019-08-03T08:45:00+02:00</lastmod>

14
sql/grant_ip.html
View File

@ -130,17 +130,17 @@
* localhost</p> * localhost</p>
<p>The program you are using to connect is not indentifying itself as 127.0.0.1 or localhost. You will have to verify the IP access it's being identified as, then add that to your grant table.</p> <p>The program you are using to connect is not indentifying itself as 127.0.0.1 or localhost. You will have to verify the IP access it's being identified as, then add that to your grant table.</p>
<p>In order to add grant an IP address you can use the following commands :</p> <p>In order to add grant an IP address you can use the following commands :</p>
<div class="highlight"><pre><span></span>GRANT ALL ON *.* TO &#39;user&#39;@&#39;computer.host.com&#39;; <div class="highlight"><pre><span></span><span class="k">GRANT</span> <span class="k">ALL</span> <span class="k">ON</span> <span class="o">*</span><span class="p">.</span><span class="o">*</span> <span class="k">TO</span> <span class="s1">&#39;user&#39;</span><span class="o">@</span><span class="s1">&#39;computer.host.com&#39;</span><span class="p">;</span>
GRANT ALL ON *.* TO &#39;user&#39;@&#39;192.168.1.6&#39;; <span class="k">GRANT</span> <span class="k">ALL</span> <span class="k">ON</span> <span class="o">*</span><span class="p">.</span><span class="o">*</span> <span class="k">TO</span> <span class="s1">&#39;user&#39;</span><span class="o">@</span><span class="s1">&#39;192.168.1.6&#39;</span><span class="p">;</span>
GRANT ALL ON *.* TO &#39;user&#39;@&#39;%&#39;; <span class="k">GRANT</span> <span class="k">ALL</span> <span class="k">ON</span> <span class="o">*</span><span class="p">.</span><span class="o">*</span> <span class="k">TO</span> <span class="s1">&#39;user&#39;</span><span class="o">@</span><span class="s1">&#39;%&#39;</span><span class="p">;</span>
</pre></div> </pre></div>
<p>The <code>%</code> is a wildcard that means any IP. Be careful when using it especially on the root user.</p> <p>The <code>%</code> is a wildcard that means any IP. Be careful when using it especially on the root user.</p>
<p>If you want to remove the rights you granted, you can use the command </p> <p>If you want to remove the rights you granted, you can use the command </p>
<div class="highlight"><pre><span></span>REVOKE ALL PRIVILEGES ON *.* TO &#39;user&#39;@&#39;computer.host.com&#39;; <div class="highlight"><pre><span></span><span class="k">REVOKE</span> <span class="k">ALL</span> <span class="k">PRIVILEGES</span> <span class="k">ON</span> <span class="o">*</span><span class="p">.</span><span class="o">*</span> <span class="k">TO</span> <span class="s1">&#39;user&#39;</span><span class="o">@</span><span class="s1">&#39;computer.host.com&#39;</span><span class="p">;</span>
REVOKE ALL PRIVILEGES ON *.* TO &#39;user&#39;@&#39;192.168.1.6&#39;; <span class="k">REVOKE</span> <span class="k">ALL</span> <span class="k">PRIVILEGES</span> <span class="k">ON</span> <span class="o">*</span><span class="p">.</span><span class="o">*</span> <span class="k">TO</span> <span class="s1">&#39;user&#39;</span><span class="o">@</span><span class="s1">&#39;192.168.1.6&#39;</span><span class="p">;</span>
REVOKE ALL PRIVILEGES ON *.* FROM &#39;user&#39;@&#39;%&#39; <span class="k">REVOKE</span> <span class="k">ALL</span> <span class="k">PRIVILEGES</span> <span class="k">ON</span> <span class="o">*</span><span class="p">.</span><span class="o">*</span> <span class="k">FROM</span> <span class="s1">&#39;user&#39;</span><span class="o">@</span><span class="s1">&#39;%&#39;</span>
</pre></div> </pre></div>
</div> </div>
<aside> <aside>
@ -156,7 +156,7 @@ REVOKE ALL PRIVILEGES ON *.* FROM &#39;user&#39;@&#39;%&#39;
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
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Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

24
sql/update_table.html
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@ -135,7 +135,7 @@ The database mydatabase.db is a SQLite database already created before the examp
</pre></div> </pre></div>
<div class="highlight"><pre><span></span>&#39;Connected: @mydatabase.db&#39; <div class="highlight"><pre><span></span><span class="s1">&#39;Connected: @mydatabase.db&#39;</span><span class="w"></span>
</pre></div> </pre></div>
@ -144,8 +144,8 @@ The database mydatabase.db is a SQLite database already created before the examp
</pre></div> </pre></div>
<div class="highlight"><pre><span></span> * sqlite:///mydatabase.db <div class="highlight"><pre><span></span> <span class="o">*</span> <span class="n">sqlite</span><span class="p">:</span><span class="o">///</span><span class="n">mydatabase</span><span class="p">.</span><span class="n">db</span>
Done. <span class="n">Done</span><span class="p">.</span>
</pre></div> </pre></div>
@ -206,10 +206,10 @@ Done.
</pre></div> </pre></div>
<div class="highlight"><pre><span></span> * sqlite:///mydatabase.db <div class="highlight"><pre><span></span> <span class="o">*</span> <span class="n">sqlite</span><span class="p">:</span><span class="o">///</span><span class="n">mydatabase</span><span class="p">.</span><span class="n">db</span>
1 rows affected. <span class="mi">1</span> <span class="k">rows</span> <span class="n">affected</span><span class="p">.</span>
* sqlite:///mydatabase.db <span class="o">*</span> <span class="n">sqlite</span><span class="p">:</span><span class="o">///</span><span class="n">mydatabase</span><span class="p">.</span><span class="n">db</span>
Done. <span class="n">Done</span><span class="p">.</span>
</pre></div> </pre></div>
@ -234,10 +234,10 @@ Done.
</pre></div> </pre></div>
<div class="highlight"><pre><span></span> * sqlite:///mydatabase.db <div class="highlight"><pre><span></span> <span class="o">*</span> <span class="n">sqlite</span><span class="p">:</span><span class="o">///</span><span class="n">mydatabase</span><span class="p">.</span><span class="n">db</span>
2 rows affected. <span class="mi">2</span> <span class="k">rows</span> <span class="n">affected</span><span class="p">.</span>
* sqlite:///mydatabase.db <span class="o">*</span> <span class="n">sqlite</span><span class="p">:</span><span class="o">///</span><span class="n">mydatabase</span><span class="p">.</span><span class="n">db</span>
Done. <span class="n">Done</span><span class="p">.</span>
</pre></div> </pre></div>
@ -305,7 +305,7 @@ Done.
<footer class="footer"> <footer class="footer">
<div class="container"> <div class="container">
<p class="text-muted"> <p class="text-muted">
<center>This project contains 93 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>. <center>This project contains 94 pages and is available on <a href="https://github.com/redoules/redoules.github.io">GitHub</a>.
<br/> <br/>
Copyright &copy; Guillaume Redoulès, Copyright &copy; Guillaume Redoulès,
<time datetime="2018">2018</time>. <time datetime="2018">2018</time>.

2
tipuesearch_content.json
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