Gaussian Naive Bayes Classifier

Gaussian Naive Bayes Classifier implements the Gaussian Naive Bayes training and classification algorithm for classification. The likelihood of the features is assumed to be Gaussian. It can perform online updates to model parameters via partial_fit.

Advantages:

• It is computational efficient
• It performs well on small amounts of data
• It can handle irrelevant features nicely

Disadvantages:

• It has a strong assumption based on the shape of data
• It is not stable