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From Sean Owen <sro...@gmail.com>
Subject Re: Mixing simiarity measures
Date Sun, 20 May 2012 04:11:04 GMT
On Sun, May 20, 2012 at 2:31 AM, Mugoma Joseph Okomba <mugoma@yengas.com> wrote:
> E.g we use PearsonCorrelationSimilarity to get similarity between users
> but find that only overlaps in ratings between the 2 users are being
> considered in final result, without consideration of the overall
> population.

Yes, this is how Pearson is defined.


> However, instead of resorting to a different measure, e.g.
> LogLikelihoodSimilarity or TanimotoCoefficientSimilarity, we are of
> opinion that we mix 2 or 3 measures so that weakness of one is booted by
> strength of the other.

The values output by different metrics are not necessarily comparable.
It would work, in the sense that it would run without error. It may
become harder to understand what the result means though.

I would simply use a different metric like LogLikelihoodSimilarity,
and stop there.

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