Right now Scikit-Learn provides several Naive Bayes models.

• GaussianNB: For continuous features that are assumed to be Gaussian distributed.
• MultinomialNB: For discreet features that are multinomially distributed, e.g. counts of words of occurrences
• BernoulliNB: For indicator features (True/False) which are assumed to be Bernoulli distributed

The obvious thing that is missing is a variant for categorical features like color for instance. It is of course possible to use dummy encoding to transform a categorical feature into indicator features for each category but this breaks the categorical correlation. If a car is red, it obviously isn't green and yellow.

So long story short, are there any plans to add a CategoricalNB? Would you like to see a PR? Or am I missing here something obvious?