Hello guys,
I am trying to run the following dummy example for Spark,
on a dataset of 250MB, using 5 machines with 10GB RAM
each, but the join seems to be taking too long ( 2hrs).
I am using Spark 0.8.0 but I have also tried the same example
on more recent versions, with the same results.
Do
RMSE = 1.467238593043199
I'm not sure what the difference is. I looked at your modifications
and they seem very similar. Is it the data you're using?
On Wed, Nov 26, 2014 at 3:34 PM, Kostas Kloudas kklou...@gmail.com wrote:
For the training I am using the code in the MovieLensALS example
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
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
On Nov 26, 2014, at 2:41 PM, Sean Owen so...@cloudera.com wrote:
How are you computing RMSE?
and how are you training the model -- not with trainImplicit right?
I wonder if you are somehow optimizing something besides RMSE.
On Wed, Nov 26, 2014 at 2:36 PM, Kostas Kloudas kklou...@gmail.com wrote
