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