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From Sean Owen <sro...@gmail.com>
Subject Re: Problems with Mahout's RecommenderIRStatsEvaluator
Date Sat, 16 Feb 2013 21:34:56 GMT
I understand the idea, but this boils down to the current implementation,
plus going back and throwing out some additional training data that is
lower rated -- it's neither in test or training. Anything's possible, but I
do not imagine this is a helpful practice in general.


On Sat, Feb 16, 2013 at 10:29 PM, Tevfik Aytekin
<tevfik.aytekin@gmail.com>wrote:

> I'm suggesting the second one. In that way the test user's ratings in
> the training set will compose of both low and high rated items, that
> prevents the problem pointed out by Ahmet.
>
> On Sat, Feb 16, 2013 at 11:19 PM, Sean Owen <srowen@gmail.com> wrote:
> > If you're suggesting that you hold out only high-rated items, and then
> > sample them, then that's what is done already in the code, except without
> > the sampling. The sampling doesn't buy anything that I can see.
> >
> > If you're suggesting holding out a random subset and then throwing away
> the
> > held-out items with low rating, then it's also the same idea, except
> you're
> > randomly throwing away some lower-rated data from both test and train. I
> > don't see what that helps either.
> >
> >
> > On Sat, Feb 16, 2013 at 9:41 PM, Tevfik Aytekin <
> tevfik.aytekin@gmail.com>wrote:
> >
> >> What I mean is you can choose ratings randomly and try to recommend
> >> the ones above  the threshold
> >>
> >>
>

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