Guillaume Redoulès

Article Recommander

  2. Machine Learning
  3. Basics
import pandas as pd
import numpy as np
%matplotlib inline

Loading data and preprocessing

we first learn the pickled article database. We will be cleaning it and separating the interesting articles from the uninteresting ones. 

df = pd.read_pickle('./article.pkl')
del df["html"]
del df["image"]
del df["URL"]
del df["hash"]
del df["source"]

df["label"] = df["note"].apply(lambda x: 0 if x <= 0 else 1)
df.head(5)
authors note resume texte titre label
0 [Danny Bradbury, Marco Santori, Adam Draper, M... -10.0 Black Market Reloaded, a black market site tha... Black Market Reloaded, a black market site tha... Black Market Reloaded back online after source... 0
1 [Emily Spaven, Stan Higgins, Emilyspaven] 1.0 The UK Home Office believes the government sho... The UK Home Office believes the government sho... Home Office: UK Should Create a Crime-Fighting... 1
2 [Pete Rizzo, Alex Batlin, Yessi Bello Perez, P... -10.0 Though lofty in its ideals, lead developer Dan... A new social messaging app is aiming to disrup... Gems Bitcoin App Lets Users Earn Money From So... 0
3 [Nermin Hajdarbegovic, Stan Higgins, Pete Rizz... 3.0 US satellite service provider DISH Network has... US satellite service provider DISH Network has... DISH Becomes World's Largest Company to Accept... 1
4 [Stan Higgins, Bailey Reutzel, Garrett Keirns,... -10.0 An unidentified 28-year-old man was robbed of ... An unidentified 28-year-old man was robbed of ... Bitcoin Stolen at Gunpoint in New York City Ro... 0

Basic statistics on the dataset

let's explore the dataset and extract some numbers : * the number of article liked/disliked

df["label"].value_counts()

0    879
1    324
Name: label, dtype: int64

Create the full content column

df['full_content'] = df.titre + ' ' + df.resume  #exclude the full texte of the article for the moment
df.head(1)
authors note resume texte titre label full_content
0 [Danny Bradbury, Marco Santori, Adam Draper, M... -10.0 Black Market Reloaded, a black market site tha... Black Market Reloaded, a black market site tha... Black Market Reloaded back online after source... 0 Black Market Reloaded back online after source... 
from sklearn.model_selection import train_test_split
training, testing = train_test_split(
    df,                # The dataset we want to split
    train_size=0.75,    # The proportional size of our training set
    stratify=df.label, # The labels are used for stratification
    random_state=400   # Use the same random state for reproducibility
)

training.head(5)
authors note resume texte titre label full_content
748 [Jon Brodkin] -10.0 Amazon, Reddit, Mozilla, and other Internet co... Amazon, Reddit, Mozilla, and other Internet co... Amazon and Reddit try to save net neutrality r... 0 Amazon and Reddit try to save net neutrality r...
1183 [Jon Brodkin] -10.0 (The Time Warner involved in this transaction ... A group of mostly Democratic senators led by A... Democrats urge Trump administration to block A... 0 Democrats urge Trump administration to block A...
769 [Joseph Brogan] -10.0 On Twitter, bad news comes at all hours, with ... On Twitter, bad news comes at all hours, with ... Some of the best art on Twitter comes from the... 0 Some of the best art on Twitter comes from the...
57 [Michael Del Castillo, Pete Rizzo, Trond Vidar... -10.0 Publicly traded online travel service Webjet i... Publicly traded online travel service Webjet i... Webjet Ethereum Pilot Targets Hotel Industry's... 0 Webjet Ethereum Pilot Targets Hotel Industry's...
892 [Andrew Cunningham] 10.0 What has changed on the 2017 MacBook, then?\nI... Andrew Cunningham\n\nAndrew Cunningham\n\nAndr... Mini-review: The 2017 MacBook could actually b... 1 Mini-review: The 2017 MacBook could actually b... 
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.svm import LinearSVC, SVC
from sklearn.pipeline import Pipeline
from sklearn.model_selection import cross_val_predict
from utils.plotting import pipeline_performance

steps = (
    ('vectorizer', TfidfVectorizer()),
    ('classifier', LinearSVC())
)
pipeline = Pipeline(steps)

predicted_labels = cross_val_predict(pipeline, training.full_content, training.label)
pipeline_performance(training.label, predicted_labels)

pipeline = pipeline.fit(training.titre, training.label)

Accuracy = 80.6%
Confusion matrix, without normalization
[[624  35]
 [140 103]]

png

import re
from utils.plotting import print_top_features
from sklearn.model_selection import GridSearchCV

def mask_integers(s):
    return re.sub(r'\d+', 'INTMASK', s)

steps = (
    ('vectorizer', TfidfVectorizer()),
    ('classifier', LinearSVC())
)

pipeline = Pipeline(steps)

gs_params = {
    #'vectorizer__use_idf': (True, False),
    'vectorizer__lowercase': [True, False],
    'vectorizer__stop_words': ['english', None],
    'vectorizer__ngram_range': [(1, 1), (1, 2), (2, 2)],
    'vectorizer__preprocessor': [mask_integers, None],
    'classifier__C': np.linspace(5,20,25)
}


gs = GridSearchCV(pipeline, gs_params, n_jobs=1)
gs.fit(training.full_content, training.label)

print(gs.best_params_)
print(gs.best_score_)

pipeline1 = gs.best_estimator_
predicted_labels = pipeline1.predict(testing.full_content)
pipeline_performance(testing.label, predicted_labels)

print_top_features(pipeline1, n_features=10)

aaa = gs.predict(testing.full_content) == testing.label 

aaa =  aaa[testing.label == 1]

testing["titre"].iloc[~aaa.values]

#pipeline1.predict(["windows xbox bitcoin"])
from sklearn.externals import joblib
joblib.dump(pipeline1, 'classifier.pkl') 

gs.predict(['Google'])

array([1], dtype=int64)

steps = (
    ('vectorizer', TfidfVectorizer()),
    ('classifier', SVC())
)

pipeline = Pipeline(steps)

gs_params = {
    #'vectorizer__use_idf': (True, False),
    'vectorizer__stop_words': ['english', None],
    'vectorizer__ngram_range': [(1, 1), (1, 2), (2, 2)],
    'vectorizer__preprocessor': [mask_integers, None],
    'classifier__C': np.linspace(5,20,25)
}


gs = GridSearchCV(pipeline, gs_params, n_jobs=1)
gs.fit(training.full_content, training.label)

print(gs.best_params_)
print(gs.best_score_)

pipeline1 = gs.best_estimator_
predicted_labels = pipeline1.predict(testing.full_content)
pipeline_performance(testing.label, predicted_labels)

print_top_features(pipeline1, n_features=10)

{'classifier__C': 5.0, 'vectorizer__ngram_range': (1, 1), 'vectorizer__preprocessor': &lt;function mask_integers at 0x00000237491B67B8&gt;, 'vectorizer__stop_words': 'english'}
0.711180124224
Accuracy = 71.2%
Confusion matrix, without normalization
[[153   0]
 [ 62   0]]



---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

&lt;ipython-input-9-3e0781e307fb&gt; in &lt;module&gt;()
     25 pipeline_performance(testing.label, predicted_labels)
     26 
---&gt; 27 print_top_features(pipeline1, n_features=10)


C:\Users\Guillaume\Documents\Code\recommandation\utils\plotting.py in print_top_features(pipeline, vectorizer_name, classifier_name, n_features)
     81 def print_top_features(pipeline, vectorizer_name='vectorizer', classifier_name='classifier', n_features=7):
     82     vocabulary = np.array(pipeline.named_steps[vectorizer_name].get_feature_names())
---&gt; 83     coefs = pipeline.named_steps[classifier_name].coef_[0]
     84     top_feature_idx = np.argsort(coefs)
     85     top_features = vocabulary[top_feature_idx]


C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\svm\base.py in coef_(self)
    483     def coef_(self):
    484         if self.kernel != 'linear':
--&gt; 485             raise ValueError('coef_ is only available when using a '
    486                              'linear kernel')
    487


ValueError: coef_ is only available when using a linear kernel

png

from sklearn.naive_bayes import BernoulliNB


steps = (
    ('vectorizer', TfidfVectorizer()),
    ('classifier', BernoulliNB())
)

pipeline2 = Pipeline(steps)

gs_params = {
    'vectorizer__stop_words': ['english', None],
    'vectorizer__ngram_range': [(1, 1), (1, 2), (2, 2)],
    'vectorizer__preprocessor': [mask_integers, None],
    'classifier__alpha': np.linspace(0,1,5),
    'classifier__fit_prior': [True, False]
}

gs = GridSearchCV(pipeline2, gs_params, n_jobs=1)
gs.fit(training.full_content, training.label)

print(gs.best_params_)
print(gs.best_score_)

pipeline2 = gs.best_estimator_
predicted_labels = pipeline2.predict(testing.full_content)
pipeline_performance(testing.label, predicted_labels)

print_top_features(pipeline2, n_features=10)

C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:820: RuntimeWarning: divide by zero encountered in log
  neg_prob = np.log(1 - np.exp(self.feature_log_prob_))
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:823: RuntimeWarning: invalid value encountered in add
  jll += self.class_log_prior_ + neg_prob.sum(axis=1)
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:801: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -


{'classifier__alpha': 0.25, 'classifier__fit_prior': True, 'vectorizer__ngram_range': (1, 1), 'vectorizer__preprocessor': &lt;function mask_integers at 0x00000237491B67B8&gt;, 'vectorizer__stop_words': 'english'}
0.805900621118
Accuracy = 78.1%
Confusion matrix, without normalization
[[140  13]
 [ 34  28]]
Top like features:
['use' 'just' 'year' 'price' 'time' 'Bitcoin' 'bitcoin' 'new' 'The'
 'INTMASK']
---
Top dislike features:
['ABBA' 'cable' 'cab' 'byte' 'publication' 'bye' 'publications' 'publicity'
 'buyer' 'publicizing']

png

from sklearn.naive_bayes import MultinomialNB


steps = (
    ('vectorizer', TfidfVectorizer()),
    ('classifier', MultinomialNB())
)

pipeline3 = Pipeline(steps)

gs_params = {
    'vectorizer__stop_words': ['english', None],
    'vectorizer__ngram_range': [(1, 1), (1, 2), (2, 2)],
    'vectorizer__preprocessor': [mask_integers, None],
    'classifier__alpha': np.linspace(0,1,5),
    'classifier__fit_prior': [True, False]
}

gs = GridSearchCV(pipeline3, gs_params, n_jobs=1)
gs.fit(training.full_content, training.label)

print(gs.best_params_)
print(gs.best_score_)

pipeline3 = gs.best_estimator_
predicted_labels = pipeline3.predict(testing.full_content)
pipeline_performance(testing.label, predicted_labels)

print_top_features(pipeline3, n_features=10)

C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -
C:\Users\Guillaume\Anaconda3\lib\site-packages\sklearn\naive_bayes.py:699: RuntimeWarning: divide by zero encountered in log
  self.feature_log_prob_ = (np.log(smoothed_fc) -


{'classifier__alpha': 0.5, 'classifier__fit_prior': False, 'vectorizer__ngram_range': (1, 1), 'vectorizer__preprocessor': &lt;function mask_integers at 0x00000237491B67B8&gt;, 'vectorizer__stop_words': 'english'}
0.80900621118
Accuracy = 79.1%
Confusion matrix, without normalization
[[141  12]
 [ 33  29]]
Top like features:
['time' 'Google' 'Pro' 'Apple' 'new' 'The' 'Bitcoin' 'price' 'bitcoin'
 'INTMASK']
---
Top dislike features:
['ABBA' 'categories' 'catching' 'catalyst' 'catalog' 'casually' 'casts'
 'cast' 'cashier' 'ran']

png