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feature importance naive bayes python

Famous Flamingo answered on May 8, 2021 Popularity 8/10 Helpfulness 4/10

answer feature importance naive bayes python

feature importance naive bayes python

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neg_class_prob_sorted = NB_optimal.feature_log_prob_[0, :].argsort()[::-1]
pos_class_prob_sorted = NB_optimal.feature_log_prob_[1, :].argsort()[::-1]

print(np.take(count_vect.get_feature_names(), neg_class_prob_sorted[:10]))
print(np.take(count_vect.get_feature_names(), pos_class_prob_sorted[:10]))

Popularity 8/10 Helpfulness 4/10 Language python

Source: stackoverflow.com

Tags: python

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