Naive Bayes Classifier tips

In a nutshell, the Gaussian Naive Bayes model is generally used for continuous data (where each feature is a real number), where the underlying data distribution is assumed to be a Gaussian (Normal) distribution.

The Multinomial Naive Bayes model counts how often a certain event occurs in the dataset (for example how often a certain word occurs in a document).

The Bernoulli Naive Bayes model is similar to the Multinomial Naive Bayes model, but instead of counting how often an event occurred, it only describes whether or not an event occurred (for example whether or not a certain word occurs in a document, where it doesn't matter if it occurs once or 100000 times)