The Naive Bayes algorithm is a classification technique that is based on the Bayes' Theorem. It assumes that the predictors are independent of each other. A Naive Bayes classifier assumes that the presence of a certain feature in a class is not related to the presence of any other feature. For example, the apple fruit is characterized by red color, round shape, and about 3 inches of diameter. Although these features depend on each other, they independently contribute to the probability of the fruit being an apple.

Regression analysis is a technique used to determine the relationship between the dependent and the independent variable (s) for prediction purposes. It is a good tool for data modelling and analysis. There are different regression techniques. Our focus will be on Logistic Regression. Logistic Regression is suitable when there are more than one independent variables in a dataset.