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From Sean Owen <sro...@gmail.com>
Subject Re: Remove unused recommenders?
Date Thu, 06 Dec 2012 15:14:42 GMT
The tree-based ones are very old and not fast, and were more of an
experiment. I recall a few questions about them but it seemed like
people were really just trying to do clustering, and this is a bad way
to do clustering.

knn is old too, and in a sense spiritually quite similar to ALS. I
don't mind removing it either.

It would seal it if there were even a nominal argument that this
improves the rest of the code base -- less to maintain, removes
duplication, inconsistency, etc. I could imagine that argument here.

On Thu, Dec 6, 2012 at 3:06 PM, Sebastian Schelter <ssc@apache.org> wrote:
> Hi there,
>
> I'm currently thinking whether we should do a little cleanup in the
> non-distributed recommenders package and throw out recommenders that
> have not been used/asked about on the mailinglist or that have been
> replaced by a superior implementation.
>
> If anyone reads this and sees a recommender, he/she wants to be kept,
> please shout!
>
> /s
>
> Here's a list of suggested stuff to remove, let me know what you think:
>
> org.apache.mahout.cf.taste.impl.recommender.svd.FunkSVDFactorizer
>
> RatingSGDFactorizer should be learning faster and has a nicer model as
> it includes user/item biases
>
>
> org.apache.mahout.cf.taste.impl.recommender.svd.ImplicitLinearRegressionFactorizer
>
> Seems to be using the same model as ALSWRFactorizer, however there are
> no tests and ALSWR can handle more explicit and implicit feedback
>
>
> org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
> org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
> org.apache.mahout.cf.taste.impl.recommender.knn
>
> I don't recall anybody using those or asking about them the last years.
>
>
>

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