There have been many people asking about contributing recommender systems
to scikit-learn, and generally the response has been that it doesn't quite
fit in with the library. Though it can be shoehorned somewhat perhaps, I
recommend you take a look at https://github.com/mendeley/mrec, which
implements a number of recommender algorithms, depends in part on
scikit-learn, and tries where possible to conform to the scikit-learn API.
Nick
On Mon, Feb 3, 2014 at 3:23 AM, nmura...@masonlive.gmu.edu <
nmura...@masonlive.gmu.edu> wrote:
> This is in response to the thread on recommender system implementation
> in scikit-learn. I would also like to know if any of the scikit-learn
> contributors are willing to mentor a project which implements basic
> recommender system algorithms - collaborative filtering
> (user-based/item-based/matrix factorization) for Google Summer of Code. I
> feel the lack of a scalable, extensible open-source recommendation engine
> in python is an interesting gap to fill and would like to try my hand at it
> during GSOC. There are a couple of interesting problems to address in this
> case like how to design a recommendation engine that conforms to the design
> of scikit-learn package as much as possible. Some of the other challenges
> are implementing support for Sparse matrix operations.
>
> Thanks,
> Nikhil
>
> ------------------------------
> *From:* MIT SHAH [mitk1s...@gmail.com]
> *Sent:* Sunday, February 02, 2014 9:39 AM
> *To:* scikit-learn-general@lists.sourceforge.net
> *Subject:* [Scikit-learn-general] Contributing in a New Topic :
> Recommender Systems
>
> Hi,
>
> I want to know whether there are algorithms on "Recommender
> Systems" in scikit-learn. I didn't found this topic in documentation. If
> not, I would like to contribute on this topic.
> Please guide me.
>
> Thanks !!
>
>
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