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Posted to dev@mahout.apache.org by "Lance Norskog (JIRA)" <ji...@apache.org> on 2011/03/24 06:56:05 UTC
[jira] [Commented] (MAHOUT-586) Redo RecommenderEvaluator for
modularity
[ https://issues.apache.org/jira/browse/MAHOUT-586?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13010566#comment-13010566 ]
Lance Norskog commented on MAHOUT-586:
--------------------------------------
(The MAHOUT-586 of March 15 has the SamplingDataModel classes)
I was working with a datamodel that did its own recommendations.
The original preference-based api (AbstractDifference)RecommenderEvaluator api does not allow for comparing a data model with a recommender or another data model. AbstractDifference... with a little refactoring does this using its existing sampling code. I've sent my version of this to a couple of people on the list, because they wanted to evaluate a datamodel against something. If you adopt this refactoring, the api becomes much more usable. Also much faster than my rearrangement :)
Second, I was working with a datamodel that did not give numbers at all. Order-based seemed the right way, but far too many algorithms presented themselves.
The problem with this patch is that I have not posted these recommenders, so it all seems pointless. But believe me you, there's a reason for my pointlessness :)
> Redo RecommenderEvaluator for modularity
> ----------------------------------------
>
> Key: MAHOUT-586
> URL: https://issues.apache.org/jira/browse/MAHOUT-586
> Project: Mahout
> Issue Type: Improvement
> Components: Collaborative Filtering
> Reporter: Lance Norskog
> Assignee: Sean Owen
> Fix For: 0.5
>
> Attachments: MAHOUT-559.patch, MAHOUT-586.patch, MAHOUT-586.patch, MAHOUT-586.patch
>
>
> The RecommenderEvaluator implementation is hard-coded around one algorithm.
> This is a more flexible, modular rewrite.
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