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From Sebastian Schelter <...@apache.org>
Subject Re: RecommenderJob in mahout-0.4 returning 1.0 score for each recommendation
Date Fri, 26 Nov 2010 18:45:53 GMT
Hi Sean,

the prediction computation for boolean data is done in
AggregateAndRecommendReducer.reduceBooleanData()

It computes *all* possible items to recommend for the current user and
writes out only the n first after that, with n being the number
specified in the parameter --numRecommendations given to RecommenderJob.

Can you point me to the code where the non-distributed code handles the
problem of ranking them? We could certainly emulate that behaviour in
the distributed code too.

--sebastian



Am 26.11.2010 19:35, schrieb Sean Owen:
> But is it then ranking the recommendations by the estimated pref? If
> it's always 1, then the ordering is not meaningful.
>
> Maybe it is, I just haven't looked at your changes in much detail
> since you made them although it looked broadly correct and proper.
>
> On Fri, Nov 26, 2010 at 6:33 PM, Sebastian Schelter <ssc@apache.org> wrote:
>   
>> If all ratings have value 1 (cause we use boolean data) the result of
>> the Predicition can also only be 1.
>>     


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