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https://issues.apache.org/jira/browse/MAHOUT-906?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13173218#comment-13173218
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Sean Owen commented on MAHOUT-906:
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OK the problem I'm still having with it, which is a small matter of
organization, is that this plucks out two unrelated pieces of code to refactor
and places them into one interface with two methods. For example it's called
"RelevantItemsDataSplitter" when that only describes 1 of the 2 roles it plays.
Can this be two interfaces, since these are two different roles conceptually?
For example the "processOneUser()" ought to be in a different interface and
have a more descriptive name I'd imagine.
If you can please use 2 spaces instead of tab for formatting.
Otherwise this is pretty uncontroversial, just pulling out some code and
leaving a hook in its place, which seems just fine.
> Allow collaborative filtering evaluators to use custom logic in splitting
> data set
> ----------------------------------------------------------------------------------
>
> Key: MAHOUT-906
> URL: https://issues.apache.org/jira/browse/MAHOUT-906
> Project: Mahout
> Issue Type: Improvement
> Components: Collaborative Filtering
> Affects Versions: 0.5
> Reporter: Anatoliy Kats
> Priority: Minor
> Labels: features
> Attachments: MAHOUT-906.patch, MAHOUT-906.patch, MAHOUT-906.patch,
> MAHOUT-906.patch, MAHOUT-906.patch
>
> Original Estimate: 48h
> Remaining Estimate: 48h
>
> I want to start a discussion about factoring out the logic used in splitting
> the data set into training and testing. Here is how things stand: There are
> two independent evaluator based classes:
> AbstractDifferenceRecommenderEvaluator, splits all the preferences randomly
> into a training and testing set. GenericRecommenderIRStatsEvaluator takes
> one user at a time, removes their top AT preferences, and counts how many of
> them the system recommends back.
> I have two use cases that both deal with temporal dynamics. In one case,
> there may be expired items that can be used for building a training model,
> but not a test model. In the other, I may want to simulate the behavior of a
> real system by building a preference matrix on days 1-k, and testing on the
> ratings the user generated on the day k+1. In this case, it's not items, but
> preferences(user, item, rating triplets) which may belong only to the
> training set. Before we discuss appropriate design, are there any other use
> cases we need to keep in mind?
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