Naive bayes algorithm relies on bayes theorem which is stated mathematically as follows Naive Bayes algorithm is an application of Bayes’ theorem as a classification algorithm with the explicit assumption that all features or predictors are independent. The word “naive” in its name is because of the independence assumption since we know that this is not always true and features tend to be related.Naive Bayes algorithm relies on Bayes theorem which is stated mathematically as follows.With the independence assumption that all input features are unrelated, the numerator can be expressed as: Using the independence representation, Bayes theorem can be simplified to a product of probabilities.However, in our model, the input data remains constant, therefore the denominator has no effect on the model. We can choose to ignore it. Another way of thinking about it is that there is no y term in the denominator , so it does not help us in any way to predict output classes. The formula then becomes a…