As it is known that naive Bayes algorithm is mostly used for classification problems, what are the methods or technique used in order to apply naive Bayes algorithm to regression problems?
In regression, we are going to predict the outcome variable Y based on the features, X . i.e., we need to calculate P(Y|X). Using Bayes theorem, we can rewrite the above conditional probability. Then we need to estimate the joint density, P(X,Y). One of the used techniques to estimate the above joint distribution is the Kernel density estimator.