Classification *is* regression. You can always ask the result for the index of the largest score.
On Tue, Oct 23, 2012 at 7:02 AM, Timothy Mann <[email protected]>wrote: > It also seems strange that the classify method is being used for > regression. To me classification is the act of selecting a category > according to some rule. Here what classification does is calculate scores > for an instance in each category. It may make sense to add a method, for > example, > > public Vector scores(Vector); or maybe public Vector evaluate(Vector);, > etc. > > Adding a method wouldn't break older code, but it also wouldn't resolve > strange use of classifier. > > -Timothy Mann > > On Tue, Oct 23, 2012 at 5:32 AM, Grant Ingersoll <[email protected] > >wrote: > > > > > On Oct 22, 2012, at 12:20 AM, Ted Dunning wrote: > > > > > Yes. > > > > > > It seems stupid in retrospect. Changing these things is very painful, > > > however, because we have no idea how many people will be affected. > > > > That being said, we are still pre 1.0. Better to change now than to bake > > it in 1.0? > > > > > > > > On Sun, Oct 21, 2012 at 9:16 PM, Timothy Mann <[email protected] > > >wrote: > > > > > >> 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 > > >> > > > > >
