Dear Patrick,
On Mon, Mar 16, 2015 at 11:00 AM, Patrick Urbanke <
patrick-axel.urba...@wiwi.uni-goettingen.de> wrote:
> Hi,
>
>
> thank you for your responses.
>
> I did take a look at your previous work in this regard as well as the
> todo-list and it seems you've made quite some progress. That's great and
> I really look forward to seeing the final result, but to be quite honest
> with you, I'm afraid "I've added a couple of minor features to a module
> that was otherwise pretty well developed" doesn't really make for a good
> Bachelor's thesis.
Indeed, it may be too difficult, because it requires reading and
understanding other people's code and the motivation behind design choices
as well as everything about the method.
> What I would like my students to do is to develop one
> algorithm (or several algorithms) from beginning to end.
>
>
So how about we implement some more standard clustering algorithms, for
> instance c-means, DIANA or fuzzy subspace clustering? I've searched for
> these and a couple of other related keywords in the pull requests and it
> appears no is working on that yet. Correct me if I'm wrong.
>
>
Any new contribution needs to be motivated thoroughly. See
http://scikit-learn.org/stable/faq.html for criteria. The methods you
mention do appear in the mainstream literature, but it would be necessary
to pick one of them and make a case for the utility of adding it to the
code base. Acceptance criteria are so stringent because the cost of
maintenance of the code base is already very high.
> I'll talk to my student, but my guess is he'll like the idea more than
> the multilayer perceptron.
>
>
Maybe your student can apply to one of the Google Summer of Code 2015
projects?
Michael
>
> Raghav R V 於 2015/3/16 上午 07:54 寫道:
> > Also there is a PR by Andy working towards completing the same (MLP)
> > here - https://github.com/scikit-learn/scikit-learn/pull/3939
> >
> > BTW, that PR does have a nice todo list, which you might want to take
> > a look at :)
> >
> >
> >
> > R
> >
> > On Mon, Mar 16, 2015 at 2:39 AM, Joel Nothman <joel.noth...@gmail.com>
> wrote:
> >> I think #3306 (Extreme Learning Machines) needs review, and after that's
> >> merged, focus should return to the MLP PR. I've not been following
> either of
> >> those PRs extremely closely, but I gather that both are quite mature,
> but
> >> not small items for review.
> >>
> >> On 16 March 2015 at 07:53, Michael Eickenberg <
> michael.eickenb...@gmail.com>
> >> wrote:
> >>> Maybe others can comment on the status of this PR and to what extent
> help
> >>> may be needed to finish it?
> >>>
> >>> Michael
> >>>
> >>> On Sun, Mar 15, 2015 at 9:47 PM, Michael Eickenberg
> >>> <michael.eickenb...@gmail.com> wrote:
> >>>> Dear Patrick,
> >>>>
> >>>> there is an almost finished pull request for multilayer perceptrons
> from
> >>>> last years GSoC by Issam Laradji:
> >>>> https://github.com/scikit-learn/scikit-learn/pull/3204
> >>>>
> >>>> Michael
> >>>>
> >>>> On Sun, Mar 15, 2015 at 8:57 PM, Patrick Urbanke
> >>>> <patrick-axel.urba...@wiwi.uni-goettingen.de> wrote:
> >>>>> Hello,
> >>>>>
> >>>>>
> >>>>> I'm writing, because I would like to contribute a multilayer
> perceptron
> >>>>> module to scikit-learn. On your website it says that I should contact
> >>>>> you to avoid duplicating work, so here I am.
> >>>>>
> >>>>> I'm a research associate and PhD candidate at the University of
> >>>>> Göttingen, Germany. All of my research is related to machine learning
> >>>>> and I often use scikit-learn to benchmark my own algorithms. I also
> use
> >>>>> scikit-learn for teaching, so thank you for all for your great work.
> >>>>>
> >>>>> I've noticed that scikit-learn still lacks a multilayer perceptron.
> >>>>> Since this is a very popular algorithm, I've decided that it would
> be a
> >>>>> good idea to have one of my students develop such a module for his
> >>>>> Bachelor's thesis under my supervision. He is very talented and I
> have
> >>>>> no doubt that he can do it. Also, he can build on some code I have
> have
> >>>>> already written.
> >>>>>
> >>>>> Here are the functionalities we would implement:
> >>>>> - Classifier and regressor
> >>>>> - Trained using SGD with minibatch updating
> >>>>> - One hidden layer
> >>>>> - Different activation functions (sigmoid, tanh, Gaussian RBM,
> >>>>> multiquadric RBM, linear) and the ability to mix them (so you could
> have
> >>>>> a neural network with 5 sigmoid functions, 10 Gaussian RBM and 5
> >>>>> multiquadric RBM)
> >>>>> - L2 regularization
> >>>>>
> >>>>> Nice to have:
> >>>>> - Support for scipy sparse matrices
> >>>>>
> >>>>> We would develop the main functionalities in C++ and then write an
> >>>>> interface using Cython. Obviously, we would adhere to the coding
> >>>>> guidelines
> >>>>>
> >>>>> (
> http://scikit-learn.org/stable/developers/index.html#coding-guidelines).
> >>>>>
> >>>>> Anything else we should consider?
> >>>>>
> >>>>>
> >>>>> Greetings,
> >>>>> Patrick Urbanke
> >>>>>
> >>>>>
> >>>>>
> >>>>>
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