Sean, I did this just to test the model. When I do a split of my data as training to 80% and test to be 20%
I get a Root-mean-square error = NaN So I am wondering where I might be going wrong Regards, VG On Sun, Jul 24, 2016 at 12:12 AM, Sean Owen <so...@cloudera.com> wrote: > No, that's certainly not to be expected. ALS works by computing a much > lower-rank representation of the input. It would not reproduce the > input exactly, and you don't want it to -- this would be seriously > overfit. This is why in general you don't evaluate a model on the > training set. > > On Sat, Jul 23, 2016 at 7:37 PM, VG <vlin...@gmail.com> wrote: > > I am trying to run ml.ALS to compute some recommendations. > > > > Just to test I am using the same dataset for training using ALSModel and > for > > predicting the results based on the model . > > > > When I evaluate the result using RegressionEvaluator I get a > > Root-mean-square error = 1.5544064263236066 > > > > I thin this should be 0. Any suggestions what might be going wrong. > > > > Regards, > > Vipul >
