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Predict responses for new observations from naive Bayes classification model for incremental learning

`[`

also returns the posterior probabilities (`label`

,`Posterior`

,`Cost`

] = predict(`Mdl`

,`X`

)`Posterior`

) and predicted (expected) misclassification costs (`Cost`

) corresponding to the observations (rows) in `X`

. For each observation in `X`

, the predicted class label corresponds to the minimum expected classification cost among all classes.