Thanks Joel for clarification.
I have gone through documentation of Pull 3306. I am glad that ELM will
soon be part of scikit-learn. But It is just working as an ML algorithm,
which can be fitted to data and can predict based on the trained model. I
was considering to develop something different. My plan is to implement ELM
or its variant as an object which can be used as a layer in Deep Learning
algorithms or semi-supervised algorithms wherever possible (some of which
are not yet published, but I have developed codes on Matlab and I will soon
submit them). It may be modification of previous implementations, depending
on the code. (I haven't gone through codes yet)
What do you think about this idea ? Please give suggestion with and without
considering GSoC.
thanks
On Tue, Mar 17, 2015 at 2:31 PM, <
scikit-learn-general-requ...@lists.sourceforge.net> wrote:
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> Today's Topics:
>
> 1. GSoC2015 Improve GMM (Wei Xue)
> 2. Re: GSoC2015 Improve GMM (Andreas Mueller)
> 3. Re: How about some clustering? (Sturla Molden)
> 4. GSoC 2015 (Vishwajeet Narwal)
> 5. Re: How about some clustering? (Gael Varoquaux)
> 6. Re: GSoC 2015 (Joel Nothman)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 16 Mar 2015 16:23:33 -0400
> From: Wei Xue <xuewe...@gmail.com>
> Subject: [Scikit-learn-general] GSoC2015 Improve GMM
> To: scikit-learn-general@lists.sourceforge.net
> Message-ID:
> <CAFjfbUWUBQgw=
> eyuorh4ccb8r6988-n++jyrnuhuud3hdk_...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi groups,
>
> I am a PhD student in Florida International University, US. I am interested
> in the topic improving GMM. I draft a proposal for this topic.
>
> https://github.com/xuewei4d/scikit-learn/wiki/GSoC-2015-Proposal:-Improve-GMM
>
> Here are some questions I would like to discuss.
>
> 1. -1 for coreset. The paper(
> http://las.ethz.ch/files/feldman11scalable-long.pdf) is new and its
> citations less than 15. The application situations are on clusters,
> streaming data, which is (I think) is rare for scikit-learn.
>
> 2. Currently, I have gone over the Approximation Inference chapter in PRML
> (Bishop's machine learning book) and Blei's 2006 paper. But I have not dig
> much into the code, so I don't have a detailed reimplement plan yet. Do I
> need to add more details into the 'Theory and Implementation' part of the
> proposal?
>
> 3. Any feedback is welcome.
>
> Thanks,
> Wei Xue
> -------------- next part --------------
> An HTML attachment was scrubbed...
>
> ------------------------------
>
> Message: 2
> Date: Mon, 16 Mar 2015 16:36:09 -0400
> From: Andreas Mueller <t3k...@gmail.com>
> Subject: Re: [Scikit-learn-general] GSoC2015 Improve GMM
> To: scikit-learn-general@lists.sourceforge.net
> Message-ID: <55073eb9.3060...@gmail.com>
> Content-Type: text/plain; charset="windows-1252"
>
> Hi Wei Xue.
> I am also not very convinced by the core-set approach.
> I'd rather focus on improving the API and fixing issues in the VBGMM and
> DPGMM.
> I was hoping that Murphy's book has some more details on DPGMM, but I
> didn't find any yet. He doesn't seem to talk about variational inference
> in Dirichlet processes.
>
> So far I think your proposal looks solid.
> It would be great if you could work on some pull requests to support
> your application.
>
> Best,
> Andy
>
>
> On 03/16/2015 04:23 PM, Wei Xue wrote:
> > Hi groups,
> >
> > I am a PhD student in Florida International University, US. I am
> > interested in the topic improving GMM. I draft a proposal for this topic.
> >
> https://github.com/xuewei4d/scikit-learn/wiki/GSoC-2015-Proposal:-Improve-GMM
> >
> > Here are some questions I would like to discuss.
> >
> > 1. -1 for coreset. The
> > paper(http://las.ethz.ch/files/feldman11scalable-long.pdf) is new and
> > its citations less than 15. The application situations are on
> > clusters, streaming data, which is (I think) is rare for scikit-learn.
> >
> > 2. Currently, I have gone over the Approximation Inference chapter in
> > PRML (Bishop's machine learning book) and Blei's 2006 paper. But I
> > have not dig much into the code, so I don't have a detailed
> > reimplement plan yet. Do I need to add more details into the 'Theory
> > and Implementation' part of the proposal?
> >
> > 3. Any feedback is welcome.
> >
> > Thanks,
> > Wei Xue
> >
> >
> >
> ------------------------------------------------------------------------------
> > Dive into the World of Parallel Programming The Go Parallel Website,
> sponsored
> > by Intel and developed in partnership with Slashdot Media, is your hub
> for all
> > things parallel software development, from weekly thought leadership
> blogs to
> > news, videos, case studies, tutorials and more. Take a look and join the
> > conversation now. http://goparallel.sourceforge.net/
> >
> >
> > _______________________________________________
> > Scikit-learn-general mailing list
> > Scikit-learn-general@lists.sourceforge.net
> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
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> ------------------------------
>
> Message: 3
> Date: Tue, 17 Mar 2015 01:12:05 +0000 (UTC)
> From: Sturla Molden <sturla.mol...@gmail.com>
> Subject: Re: [Scikit-learn-general] How about some clustering?
> To: scikit-learn-general@lists.sourceforge.net
> Message-ID:
> <1669946695448247089.664062sturla.molden-gmail....@news.gmane.org>
> Content-Type: text/plain; charset=UTF-8
>
> Andreas Mueller <t3k...@gmail.com> wrote:
>
> > Well, C-Means is pretty established, but I'm not sure about the benefits
> > compared to
> > a diagonal covariance GMM.
>
> It is numerically the same, except the implied pdf is different.
>
> c-means can be faster as it does not need to evaluate trancendental
> functions, e.g. if fuzzy memberships are computed with a Bartlet window,
> but it might still yield almost the same result.
>
> Sturla
>
>
>
>
> ------------------------------
>
> Message: 4
> Date: Tue, 17 Mar 2015 12:48:39 +0530
> From: Vishwajeet Narwal <vnarwa...@gmail.com>
> Subject: [Scikit-learn-general] GSoC 2015
> To: scikit-learn-general@lists.sourceforge.net
> Message-ID:
> <
> calp21m-x-rnmvacfcgnb5rf9oadwku1nyp+ybznike2qoz7...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Everyone,
>
> I am a sophomore pursuing my B.Tech in Computer Science and Engineering
> having significant experience in Machine Learning and ANN. I am working on
> a independent(for now) python library for several variants of extreme
> Learning machine, some of which I have already implemented in Matlab and
> python. Variants will include some Deep Learning and semi-supervised
> algorithms also.
>
> Is there any scope of it being part of scikit-learn, and getting this
> proposal accepted in GSoC 2015 ?
> If yes, Then I would prepare a more detailed proposal.
>
>
>
>
> thanks
>
> --
> *Vishwajeet Narwal*
> Event Organiser,IEEE LNMIIT SB
> Core Member, SRIG Research Interest Group
> DIP Mentor, Phoenix Club,LNMIIT
> 2nd Year, Computer Science & Engineering
> The *LNMIIT, Jaipur*
> -------------- next part --------------
> An HTML attachment was scrubbed...
>
> ------------------------------
>
> Message: 5
> Date: Tue, 17 Mar 2015 08:39:33 +0100
> From: Gael Varoquaux <gael.varoqu...@normalesup.org>
> Subject: Re: [Scikit-learn-general] How about some clustering?
> To: scikit-learn-general@lists.sourceforge.net
> Message-ID: <20150317073933.gk2080...@phare.normalesup.org>
> Content-Type: text/plain; charset=iso-8859-1
>
> On Tue, Mar 17, 2015 at 01:12:05AM +0000, Sturla Molden wrote:
> > c-means can be faster as it does not need to evaluate trancendental
> > functions, e.g. if fuzzy memberships are computed with a Bartlet window,
> > but it might still yield almost the same result.
>
> Being faster is a good thing. Do you have an idea of how much faster?
>
> Ga?l
>
>
>
> ------------------------------
>
> Message: 6
> Date: Tue, 17 Mar 2015 20:01:14 +1100
> From: Joel Nothman <joel.noth...@gmail.com>
> Subject: Re: [Scikit-learn-general] GSoC 2015
> To: scikit-learn-general <scikit-learn-general@lists.sourceforge.net>
> Message-ID:
> <CAAkaFLXtWxWMF=
> vx0mnhywzwwe6sux__93imueod7rafx0k...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> An ELM implementation from GSOC 2014 is awaiting review before merge, i.e.
> it's very close to inclusion. Perhaps you could contribute comments at
> https://github.com/scikit-learn/scikit-learn/pull/3306, but I don't think
> another contribution of ELMs would be appropriate.
>
> Also, the best persuasion that you are a good candidate for the job is to
> make contributions to the project in advance of application. Thus the
> project's core developers get to know you and are assured you understand
> the structure of the codebase, the API and the contribution workflow.
>
> On 17 March 2015 at 18:18, Vishwajeet Narwal <vnarwa...@gmail.com> wrote:
>
> > Hi Everyone,
> >
> > I am a sophomore pursuing my B.Tech in Computer Science and Engineering
> > having significant experience in Machine Learning and ANN. I am working
> on
> > a independent(for now) python library for several variants of extreme
> > Learning machine, some of which I have already implemented in Matlab and
> > python. Variants will include some Deep Learning and semi-supervised
> > algorithms also.
> >
> > Is there any scope of it being part of scikit-learn, and getting this
> > proposal accepted in GSoC 2015 ?
> > If yes, Then I would prepare a more detailed proposal.
> >
> >
> >
> >
> > thanks
> >
> > --
> > *Vishwajeet Narwal*
> > Event Organiser,IEEE LNMIIT SB
> > Core Member, SRIG Research Interest Group
> > DIP Mentor, Phoenix Club,LNMIIT
> > 2nd Year, Computer Science & Engineering
> > The *LNMIIT, Jaipur*
> >
> >
> >
> ------------------------------------------------------------------------------
> > Dive into the World of Parallel Programming The Go Parallel Website,
> > sponsored
> > by Intel and developed in partnership with Slashdot Media, is your hub
> for
> > all
> > things parallel software development, from weekly thought leadership
> blogs
> > to
> > news, videos, case studies, tutorials and more. Take a look and join the
> > conversation now. http://goparallel.sourceforge.net/
> > _______________________________________________
> > Scikit-learn-general mailing list
> > Scikit-learn-general@lists.sourceforge.net
> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> >
> >
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>
> ------------------------------------------------------------------------------
> Dive into the World of Parallel Programming The Go Parallel Website,
> sponsored
> by Intel and developed in partnership with Slashdot Media, is your hub for
> all
> things parallel software development, from weekly thought leadership blogs
> to
> news, videos, case studies, tutorials and more. Take a look and join the
> conversation now. http://goparallel.sourceforge.net/
>
> ------------------------------
>
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> Scikit-learn-general@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
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>
> End of Scikit-learn-general Digest, Vol 62, Issue 43
> ****************************************************
>
--
*Vishwajeet Narwal*
Event Organiser,IEEE LNMIIT SB
Core Member, SRIG Research Interest Group
DIP Mentor, Phoenix Club,LNMIIT
2nd Year, Computer Science & Engineering
The *LNMIIT, Jaipur*
------------------------------------------------------------------------------
Dive into the World of Parallel Programming The Go Parallel Website, sponsored
by Intel and developed in partnership with Slashdot Media, is your hub for all
things parallel software development, from weekly thought leadership blogs to
news, videos, case studies, tutorials and more. Take a look and join the
conversation now. http://goparallel.sourceforge.net/
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