[jira] [Comment Edited] (MAHOUT-1106) SVD++

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

    [ https://issues.apache.org/jira/browse/MAHOUT-1106?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13560094#comment-13560094 ] 

Agnonchik edited comment on MAHOUT-1106 at 1/23/13 7:44 AM:
------------------------------------------------------------

1. I compared the accuracy of biased SVD and SVD++ factorizers on the 1M MovieLens dataset and found no significant difference. Seems that both methods end up with the same RMSE but SVD++ is much slower. There should be some datasets on which SVD++  shines. What are those cases?

2. Do you think it would be natural to extend functionality of SVD++ to the case when the implicit feedback is wider than the explicit? I'm asking because a subset of items evaluated by a user implicitly quite often exceeds the rated items (N(u) and R(u) in Yehuda Koren's notations).

Thanks!
                
      was (Author: agnonchik):
    1. I compared the accuracy of biased SVD and SVD++ factorizers on the 1M MovieLens dataset and found no significant difference. Seems that both methods end up with the same RMSE and SVD++ is much more slower. There should be some datasets on which SVD++  shines. What are those cases?

2. Do you think it would be natural to extend functionality of SVD++ to the case when the implicit feedback is wider than the explicit? I'm asking because a subset of items evaluated by a user implicitly quite often exceeds the rated items (N(u) and R(u) in Yehuda Koren's notations).
                  
> SVD++
> -----
>
>                 Key: MAHOUT-1106
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1106
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Collaborative Filtering
>            Reporter: Zeno Gantner
>            Assignee: Sebastian Schelter
>         Attachments: SVDPlusPlusFactorizer.java
>
>
> Initial shot at SVD++.
> Relies on the RatingsSGDFactorizer class introduced in MAHOUT-1089.
> One could also think about several enhancements, e.g. having separate regularization constants for user and item factors.
> I am also the author of the SVDPlusPlus class in MyMediaLite, so if there are any similarities, no need to worry -- I am okay with relicensing this to the Apache 2.0 license.
> https://github.com/zenogantner/MyMediaLite/blob/master/src/MyMediaLite/RatingPrediction/SVDPlusPlus.cs

--
This message is automatically generated by JIRA.
If you think it was sent incorrectly, please contact your JIRA administrators
For more information on JIRA, see: http://www.atlassian.com/software/jira