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From Sean Owen <sro...@gmail.com>
Subject Re: problems with GenericRecommenderIRStatsEvaluator:
Date Thu, 05 Nov 2009 13:14:21 GMT
You are again partly describing what RecommenderEvaluator does, not
RecommenderIRStatsEvaluator.

The main difference between what you are describing, and what happens,
is there is no "70%" -- instead there is a relevance threshold.
However in *RecommenderEvaluator* there is a parameter than controls
what percent of data is used for training. But you are not using this
code.

What ranking are you talking about, that is ignored?

Sean

On Thu, Nov 5, 2009 at 1:08 PM, michal shmueli <michal.shmueli@gmail.com> wrote:
> The way i envision this is the follow: assume user rates 10 items, this 10
> are the correct items. Further assume that for recommendation we use subset
> of this 10 items, say 70% (leave us with 30% for test) to build the
> similarity, etc. Now, during evaluation, we ask from the recommneder for say
> k items, and we check how many from the 3 correct item (the 30% of the
> tests) are within the k recommended items.
> This solutions ignore the ranking on the different items, however, this
> could be also added later.
>
> Does it make sense?
>
> thanks,
> Michal

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