No, ALS is not modeling probabilities. The outputs are reconstructions of a 0/1 matrix. Most values will be in [0,1], but, it's possible to get values outside that range.
On Thu, Dec 15, 2016 at 10:21 PM Manish Tripathi <tr.man...@gmail.com> wrote: > Hi > > ran the ALS model for implicit feedback thing. Then I used the .transform > method of the model to predict the ratings for the original dataset. My > dataset is of the form (user,item,rating) > > I see something like below: > > predictions.show(5,truncate=False) > > > Why is the last prediction value negative ?. Isn't the transform method > giving the prediction(probability) of seeing the rating as 1?. I had counts > data for rating (implicit feedback) and for validation dataset I binarized > the rating (1 if >0 else 0). My training data has rating positive (it's > basically the count of views to a video). > > I used following to train: > > * als = ALS(rank=x, maxIter=15, regParam=y, implicitPrefs=True,alpha=40.0)* > > * model=als.fit(self.train)* > > What does negative prediction mean here and is it ok to have that? > ᐧ >
