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https://issues.apache.org/jira/browse/MAHOUT-586?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13010566#comment-13010566
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Lance Norskog edited comment on MAHOUT-586 at 3/24/11 5:54 AM:
---------------------------------------------------------------

(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 this 
pointlessness :)



      was (Author: lancenorskog):
    (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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