Naïve bayes is a method of supervised machine learning algorithm and it is from the family of probabilistic classifiers. It is simply a process of predicting the value of a feature variable independent of other features or variables that is the reason it is called naive. Here we are going to see how bayes theorem works with the very easy example of cards and then how this algorithm works on a real dataset or some set of features. Let’s dive in Naïve bayes.
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