Regarding clustering algorithms, I would suggest to have a look at convex
formulations, that can be advantageous for the sake of convergence/stability,
wrt standard algorithms that never have any guarantee. Among others: -
http://www.icml-2011.org/papers/419_icmlpaper.pdf -
http://www.google.fr/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CCkQFjAA&url=http%3A%2F%2Fpeople.csail.mit.edu%2Fpolina%2Fpapers%2FLashkariGolland_NIPS07.pdf&ei=4Ip1T-eUHYK90QWV6NjHDQ&usg=AFQjCNFCTuLQ2q1j9LBz3TPlV5Bdf6TZXQ&sig2=bpzB9HSYc3OI1ICnWY92Og
I must say however, that I haven't looked in detail to those, and I'm not sure
which one should be preferred. The pros and cons of each each algo should be
discussed as a preliminary step. I'm not sure whether anybody has enough
hindsight on these techniques. My 2c, Bertrand ----- Mail original -----
> De: "Robert Layton" <robertlay...@gmail.com>
> À: scikit-learn-general@lists.sourceforge.net
> Envoyé: Vendredi 30 Mars 2012 07:24:25
> Objet: Re: [Scikit-learn-general] GSoC 2012 pre-application
> On 30 March 2012 16:19, Gael Varoquaux < gael.varoqu...@normalesup.org
> > wrote:
> > Hi Lee,
> > Welcome! Thanks for preparing a proposal. My impression looking at
> > it,
> > is
> > that it seems a bit light for 2.5 months of work. It is pretty much
> > centered around implementing one algorithm, weighted k-means.
> > Cheers,
> > Gael
> > On Fri, Mar 30, 2012 at 12:30:46AM -0400, Lee Zamparo wrote:
> > > Hello everyone,
> > > I'm a prospective applicant to GSoC 2012, and am drafting a
> > > proposal.
> > > I would really appreciate if you could spare some time to give me
> > > feedback. My proposal is centred around sklearn.cluster, so I
> > > would
> > > like to ask Andreas Muller, Olivier Grisel or Lars Buitinck if
> > > they
> > > would consider being potential mentors.
> > > Here is the link to the Google doc containing my application:
> > > https://docs.google.com/document/d/180TbWNahVmlLiVEUNYU9nSPPeUwJ3DY4N5b3aRXhaQo/edit
> > > Once again, I am very grateful for any advice or feedback you can
> > > provide.
> > > Thanks,
> > > Lee.
> > > ------------------------------------------------------------------------------
> > > This SF email is sponsosred by:
> > > Try Windows Azure free for 90 days Click Here
> > > http://p.sf.net/sfu/sfd2d-msazure
> > > _______________________________________________
> > > Scikit-learn-general mailing list
> > > Scikit-learn-general@lists.sourceforge.net
> > > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> > --
> > Gael Varoquaux
> > Researcher, INRIA Parietal
> > Laboratoire de Neuro-Imagerie Assistee par Ordinateur
> > NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France
> > Phone: ++ 33-1-69-08-79-68
> > http://gael-varoquaux.info
> > ------------------------------------------------------------------------------
> > This SF email is sponsosred by:
> > Try Windows Azure free for 90 days Click Here
> > http://p.sf.net/sfu/sfd2d-msazure
> > _______________________________________________
> > Scikit-learn-general mailing list
> > Scikit-learn-general@lists.sourceforge.net
> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> I agree with Gael, but also like the general idea.
> One method for increasing the scope would be to add other spectral
> clustering algorithms to the project. Then create a testing example,
> comparing them in terms of space/time/efficacy for different datasets.
> Thoughts?
> Robert
> --
> Public key at: http://pgp.mit.edu/ Search for this email address and
> select the key from "2011-08-19" (key id: 54BA8735)
> ------------------------------------------------------------------------------
> This SF email is sponsosred by:
> Try Windows Azure free for 90 days Click Here
> http://p.sf.net/sfu/sfd2d-msazure
> _______________________________________________
> Scikit-learn-general mailing list
> Scikit-learn-general@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
------------------------------------------------------------------------------
This SF email is sponsosred by:
Try Windows Azure free for 90 days Click Here
http://p.sf.net/sfu/sfd2d-msazure
_______________________________________________
Scikit-learn-general mailing list
Scikit-learn-general@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
