It seems strange to me that the classify method declared in AbstractVectorClassifier returns a vector with n-1 scores, where n is the number of categories. I understand that this decision was made for efficiency reasons, but it seems like classify is the first place where people will look in the API. Instead classifyFull provides the implementation that a user may find more intuitive. Furthermore, classifyFull does not require the assumption that the scores over all categories represent probabilities that sum to one, and is therefore more general. In fact, classify is not even implemented for the Naive Bayes implementations but classifyFull is, which was initially confusing until I understood what classify actually does. Any thoughts on this?
-Timothy Mann
