The old mllib API will use RandomForest.trainClassifier() to train a RandomForestModel; the new mllib API (AKA ML) will use RandomForestClassifier.train() to train a RandomForestClassificationModel. They will produce the same result for a given dataset.
2015-07-31 1:34 GMT+08:00 Bryan Cutler <cutl...@gmail.com>: > Hi Praveen, > > In MLLib, the major difference is that RandomForestClassificationModel > makes use of a newer API which utilizes ML pipelines. I can't say for > certain if they will produce the same exact result for a given dataset, but > I believe they should. > > Bryan > > On Wed, Jul 29, 2015 at 12:14 PM, praveen S <mylogi...@gmail.com> wrote: > >> Hi >> Wanted to know what is the difference between >> RandomForestModel and RandomForestClassificationModel? >> in Mlib.. Will they yield the same results for a given dataset? >> > >