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From "Lance Norskog (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAHOUT-586) Redo RecommenderEvaluator for modularity
Date Tue, 15 Mar 2011 08:52:29 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-586?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13006846#comment-13006846
] 

Lance Norskog commented on MAHOUT-586:
--------------------------------------

Patch walkthrough:

There are now old and new apis on RecommenderEvaluator.
The one ones are as before. The new ones match the modular toolkit.
The evaluator can be run on a datamodel v.s. a recommender or even between datamodels.
I have datamodels which by nature supply recommendations; this structure makes them easy to
work with.

Patch Structure:
Abstract...Evaluator is as before.
It has two subclasses to supply statistics tracking.
Its API is tagged obsolete.

The newer APIs support a more modular approach where the tool can implement several strategies
and the user can supply your choice of statistical tracking.

The SamplingDataModel is a component that lets this new code implement separating data for
training v.s. test.This implementation is sparse but not very scalable.








> 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
>
>
> The RecommenderEvaluator implementation is hard-coded around one algorithm.
> This is a more flexible, modular rewrite.

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