Introduction

Naïve Bayes algorithm is a machine learning supervised classification technique based on Bayes theorem with strong independence assumptions between the features. It is mainly used for binary or multi class classification and still remains one of the best method for Text categorization and document categorization.

For example, a vegetable may be considered to be tomato if it is red, round and 2 inches in diameter. A naive Bayes classifier considers each of these features to contribute independently to the probability that this Vegetable is a tomato, regardless of any possible correlations between the color, roundness, and diameter features.

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