Once again, the error even with the training dataset increases. The results are:
Running 1 iterations For 1 iter.: Test RMSE = 1.2447121194304893 Training RMSE = 1.2394166987104076 (34.751317636 s). Running 5 iterations For 5 iter.: Test RMSE = 1.3253957117600659 Training RMSE = 1.3206317416138509 (37.693118023000004 s). Running 9 iterations For 9 iter.: Test RMSE = 1.3255293380139364 Training RMSE = 1.3207661218210436 (41.046175661 s). Running 13 iterations For 13 iter.: Test RMSE = 1.3255295352665748 Training RMSE = 1.3207663201865092 (47.763619515 s). Running 17 iterations For 17 iter.: Test RMSE = 1.32552953555787 Training RMSE = 1.3207663204794406 (59.682361103000005 s). Running 21 iterations For 21 iter.: Test RMSE = 1.3255295355583026 Training RMSE = 1.3207663204798756 (57.210578232 s). Running 25 iterations For 25 iter.: Test RMSE = 1.325529535558303 Training RMSE = 1.3207663204798765 (65.785485882 s). Thanks a lot, Kostas > On Nov 26, 2014, at 12:04 PM, Nick Pentreath <nick.pentre...@gmail.com> wrote: > > copying user group - I keep replying directly vs reply all :) > > On Wed, Nov 26, 2014 at 2:03 PM, Nick Pentreath <nick.pentre...@gmail.com > <mailto:nick.pentre...@gmail.com>> wrote: > ALS will be guaranteed to decrease the squared error (therefore RMSE) in each > iteration, on the training set. > > This does not hold for the test set / cross validation. You would expect the > test set RMSE to stabilise as iterations increase, since the algorithm > converges - but not necessarily to decrease. > > On Wed, Nov 26, 2014 at 1:57 PM, Kostas Kloudas <kklou...@gmail.com > <mailto:kklou...@gmail.com>> wrote: > Hi all, > > I am getting familiarized with Mllib and a thing I noticed is that running > the MovieLensALS > example on the movieLens dataset for increasing number of iterations does not > decrease the > rmse. > > The results for 0.6% training set and 0.4% test are below. For training set > to 0.8%, the results > are almost identical. Shouldn’t it be normal to see a decreasing error? > Especially going from 1 to 5 iterations. > > Running 1 iterations > Test RMSE for 1 iter. = 1.2452964343277886 (52.757125927000004 s). > Running 5 iterations > Test RMSE for 5 iter. = 1.3258973764470259 (61.183927666 s). > Running 9 iterations > Test RMSE for 9 iter. = 1.3260308117704385 (61.84948875800001 s). > Running 13 iterations > Test RMSE for 13 iter. = 1.3260310099809915 (73.799510125 s). > Running 17 iterations > Test RMSE for 17 iter. = 1.3260310102735398 (77.56512185300001 s). > Running 21 iterations > Test RMSE for 21 iter. = 1.3260310102739703 (79.607495074 s). > Running 25 iterations > Test RMSE for 25 iter. = 1.326031010273971 (88.631776301 s). > Running 29 iterations > Test RMSE for 29 iter. = 1.3260310102739712 (101.178383079 s). > > Thanks a lot, > Kostas > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > <mailto:user-unsubscr...@spark.apache.org> > For additional commands, e-mail: user-h...@spark.apache.org > <mailto:user-h...@spark.apache.org> > > >
