Mixing categorial and continuous data in Naive Bayes classifier using scikit-learn

Question

I\'m using scikit-learn in Python to develop a classification algorithm to predict the gender of certain customers. Amongst others, I want to use the Naive Bayes classifier

Answer 1

The simple answer: multiply result!! it's the same.

Naive Bayes based on applying Bayes’ theorem with the “naive” assumption of independence between every pair of features - meaning you calculate the Bayes probability dependent on a specific feature without holding the others - which means that the algorithm multiply each probability from one feature with the probability from the second feature (and we totally ignore the denominator - since it is just a normalizer).

so the right answer is:

1. calculate the probability from the categorical variables.
2. calculate the probability from the continuous variables.
3. multiply 1. and 2.