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https://issues.apache.org/jira/browse/MAHOUT-1272?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13701682#comment-13701682
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Peng Cheng edited comment on MAHOUT-1272 at 7/7/13 10:21 PM:
-------------------------------------------------------------
New parameter:
lambda = 0.001
rank of the rating matrix/number of features of each user/item vectors = 5
number of iterations/epochs = 20
result on movielens-10m, all evaluation uses RMSE:
Jul 07, 2013 6:18:57 PM org.slf4j.impl.JCLLoggerAdapter info
INFO: ==================Recommender With RatingSGDFactorizer:
0.8119081937625745 time spent: 36.509s===================
Jul 07, 2013 6:18:57 PM org.slf4j.impl.JCLLoggerAdapter info
INFO: ==================Recommender With ParallelSGDFactorizer:
0.8115207244832938 time spent: 8.747s====================
This is fast and accurate enough, I'm advancing to netflix prize dataset.
was (Author: peng):
New parameter:
lambda = 0.001
rank of the rating matrix/number of features of each user/item vectors = 5
number of iterations/epochs = 20
result on movielens-10m:
Jul 07, 2013 6:18:57 PM org.slf4j.impl.JCLLoggerAdapter info
INFO: ==================Recommender With RatingSGDFactorizer:
0.8119081937625745 time spent: 36.509s===================
Jul 07, 2013 6:18:57 PM org.slf4j.impl.JCLLoggerAdapter info
INFO: ==================Recommender With ParallelSGDFactorizer:
0.8115207244832938 time spent: 8.747s====================
This is fast and accurate enough, I'm advancing to netflix prize dataset.
> Parallel SGD matrix factorizer for SVDrecommender
> -------------------------------------------------
>
> Key: MAHOUT-1272
> URL: https://issues.apache.org/jira/browse/MAHOUT-1272
> Project: Mahout
> Issue Type: New Feature
> Components: Collaborative Filtering
> Reporter: Peng Cheng
> Assignee: Sean Owen
> Labels: features, patch, test
> Attachments: GroupLensSVDRecomenderEvaluatorRunner.java,
> mahout.patch, ParallelSGDFactorizer.java, ParallelSGDFactorizer.java,
> ParallelSGDFactorizerTest.java, ParallelSGDFactorizerTest.java
>
> Original Estimate: 336h
> Remaining Estimate: 336h
>
> a parallel factorizer based on MAHOUT-1089 may achieve better performance on
> multicore processor.
> existing code is single-thread and perhaps may still be outperformed by the
> default ALS-WR.
> In addition, its hardcoded online-to-batch-conversion prevents it to be used
> by an online recommender. An online SGD implementation may help build
> high-performance online recommender as a replacement of the outdated
> slope-one.
> The new factorizer can implement either DSGD
> (http://www.mpi-inf.mpg.de/~rgemulla/publications/gemulla11dsgd.pdf) or
> hogwild! (www.cs.wisc.edu/~brecht/papers/hogwildTR.pdf).
> Related discussion has been carried on for a while but remain inconclusive:
> http://web.archiveorange.com/archive/v/z6zxQUSahofuPKEzZkzl
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