Naive Bayes models assume that observations have some multivariate distribution given class membership, but the predictor or features composing the observation are independent. This framework can accommodate a complete feature set such that an observation is a set of multinomial counts.
To train a naive Bayes model, use
the command-line interface. After training, predict labels or estimate
posterior probabilities by passing the model and predictor data to
|ClassificationNaiveBayes||Naive Bayes classification|