Hi Andy.
Thanks for the response :)
I'm looking into the project ideas but I'm am unable to zero in on a single
idea for GSoC . My knowledge is limited to linear and clustering models,
however I am willing to learn and read the literature well before GSoC and
I am a pretty quick learner. It would be really nice if you or some of the
other sklearn devs, suggest a couple of more ideas (maybe 2 or 3 estimators
together or improving on existing estimators), that would help me write a
successful GSoC proposal.
Thanks again,
On Thu, Jan 30, 2014 at 2:23 AM, Andy <t3k...@gmail.com> wrote:
> Hey Manoj.
> I agree that the description is vague.
> I think what Vlad was trying to say that refurbishing only makes sense if
> it comes with long-time support by an active user.
>
> Basically, "refurbishing" means
> - have a simple and sklearn-consistent interface
> - be numerically stable, reliable and repeatable
> - serve all feasible major usecases
> - be easy to apply to the problems that people have in practice
>
> While you could certainly do the first, and probably the second given some
> familiarity,
> doing the last two is hard if you are not using the method actively in
> your day-to-day data mangling.
> And even if the implementation was refurbished, but you are not around
> afterwards, it is not clear who will be able
> to maintain it.
>
> I don't think implementing coresets is a good idea, because it is mostly
> helpful for cluster computing afaik.
> Also, it adds more abstractions on top of a suboptimal interface and
> implementation.
> Additionally, I would really like to limit the number of additional
> estimators before 1.0.
>
> If you feel up to the task of really making this a great implementation,
> and also taking care of it in the long run,
> please go ahead with the proposal. But I think that might be a bit much to
> ask for a GSoC.
>
> Cheers,
> Andy
>
> ps: only my opinion ;)
>
>
>
> On 01/18/2014 08:30 PM, Manoj Kumar wrote:
>
> Hello,
>
> I found this idea "Improving Gaussian Mixture Models" , repeating in
> 2012 and 2013, so I assumed this to be of real interest to the scikit-learn
> community. I have a fundamental knowledge of Gaussian Models, and the EM
> algorithm. I would like to take this project forward as part of GSoC. I
> took a quick look at the issues tracker, and I found a number of issues.
>
> I mailed Vlad (since his name was mentioned there as a mentor) and this
> is what he had to say
>
> "
> Hey Manoj,
>
> I just noticed I'm listed as a possible mentor for that. I think when I
> put my name there I was thinking of HMM instead of GMM, oops!
>
> I'm guessing that the module is not really maintained and it would be good
> if somebody who is involved with GMMs actively would take it under their
> wing.
>
> I guess the point of the GSoC idea that was on there was that somebody
> proposed
> to do a GSoC project to implement coresets for GMM fitting (there are two
> links
> there). I have absolutely no experience with this method.
> Of course in order to add a major new feature to a suboptimally maintained
> model,
> some refactoring needed to be listed as well.
>
> Again, my feeling is that this idea came from a potential student and it
> isn't a
> burning need. What do you think about it?
>
> Best,
> Vlad
> "
> Can someone clearly explain, what the community expects out of such a
> project, the project description ("Refurbish the current GMM code to put it
> to the scikit's standards") in the wiki page, seems a bit vague to me.
>
> Thanks.
> --
> Regards,
> Manoj Kumar,
> Mech Undergrad
> http://manojbits.wordpress.com
>
>
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--
Regards,
Manoj Kumar,
Mech Undergrad
http://manojbits.wordpress.com
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