This JIRA is to discuss refactoring NaiveBayes in order to support both discrete and continuous labels and features.
Currently, NaiveBayes supports only discrete labels and features.
Proposal: Generalize it to support continuous values as well.
Some items to discuss are:
- How commonly are continuous labels/features used in practice? (Is this necessary?)
- What should the API look like?
- E.g., should NB have multiple classes for each type of label/feature, or should it take a general Factor type parameter?