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.manish@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
>

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