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I used the Naive Bayes Classifier in both Python and R

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Naive-Bayes

Naive Bayes is based on Bayes Theorem .

Scikit learn docs

It basically first considers the point in between the two Classifiers and then tries to predict the probability to guess in which class it belongs to . Then it tries to calculate the Posterior Probability from the product of likelihood and the prior probability . We can ignore the Marginal likelihood{ p(x) } because when we compare the posterior probability ofthe different classifications then it cancels out .

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This is suitable for Sentiment Analysis problems with two output labels .

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I used the Naive Bayes Classifier in both Python and R

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