[jira] [Commented] (MAHOUT-1089) SGD matrix factorization for rating prediction with user and item biases

["Sebastian Schelter (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MAHOUT-1089?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13466659#comment-13466659 ] 

Sebastian Schelter commented on MAHOUT-1089:
--------------------------------------------

Hi Zeno,

great work! I'm polishing and testing your code a little, will commit it very soon. One question, in your code, the cached rating data is only shuffled once before the training starts. Wouldn't it be better to shuffle in each iteration?
                
> SGD matrix factorization for rating prediction with user and item biases
> ------------------------------------------------------------------------
>
>                 Key: MAHOUT-1089
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1089
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Collaborative Filtering
>            Reporter: Zeno Gantner
>            Assignee: Sebastian Schelter
>         Attachments: RatingSGDFactorizer.java
>
>
> A matrix factorization that is trained with standard SGD on all features at the same time, in contrast to ExpectationMaximizationFactorizer, which learns feature by feature.
> Additionally to the free features it models a rating bias for each user and item.

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