Hi Andy,
Thanks a lot for your feedback... I'll update my proposal wiki based on
your guidelines and also submit the same to melange too by today!
Thanks,
R
On Tue, Mar 24, 2015 at 3:10 AM, Andreas Mueller <t3k...@gmail.com> wrote:
> Hi Raghav.
>
> I feel that your proposal lacks some focus.
> I'd remove the two:
>
> Mallow's Cp for LASSO / LARS
> Implement built in abs max scaler, Nesterov's momentum and finish up the
> Multilayer Perceptron module.
>
> And as discussed in this thread probably also
> Forge a self sufficient ML tutorial based on scikit-learn.
>
> If you feel like you proposal has not enough material (not sure about
> that),
> two things that could be added and are more related to the
> cross-validation and grid-search part
> (but probably difficult from an API standpoint) are making CV objects (aka
> path algorithms, or generalized cross-validation)
> work together with GridSearchCV.
> The other would be how to allow early stopping using a validation set.
> The two are probably related (imho).
>
> Olivier also mentioned cross-validation for out-of-core (partial_fit)
> algorithms.
> I feel that is not as important, but might also tie into your proposal.
>
> Finishing the refactoring of model_evaluation in three days seems a bit
> optimistic, if you include reviews.
>
> For sample_weight support, I'm not if there are obvious ways to extend
> sample_weight to all the algorithms that you mentioned.
> How does it work for spectral clustering and agglomerative clustering for
> example?
>
> In general, I feel you should rather focus on less things, and more on the
> details of what to do there.
> Otherwise the proposal looks good.
> For the wiki, having links to the issues might be helpful.
>
> Thanks for the application :)
>
> Andy
>
> On 03/22/2015 08:52 PM, Raghav R V wrote:
>
> 2 things :
>
> * The subject should have been "Multiple Metric Support in grid_search
> and cross_validation modules and other general improvements" and not
> multiple metric learning! Sorry for that!
> * The link was not available due to the trailing "." (dot), which has been
> fixed now!
>
> Thanks
> R
>
> On Mon, Mar 23, 2015 at 5:47 AM, Raghav R V <rag...@gmail.com> wrote:
>
>> 1. the link is broken
>>>
>>
>> Ah! Sorry :) -
>> https://github.com/scikit-learn/scikit-learn/wiki/GSoC-2015-Proposal:-Multiple-metric-support-for-CV-and-grid_search-and-other-general-improvements
>> .
>>
>> 2. that sounds quite difficult and unfortunately conducive to cheating
>>>
>>
>> Hmm... Should I then simply opt for adding more examples then?
>>
>>
>>>
>>> On Sun, Mar 22, 2015 at 7:57 PM, Raghav R V <rag...@gmail.com> wrote:
>>>
>>>> Hi,
>>>>
>>>> 1. This is my proposal for the multiple metric learning project as a
>>>> wiki page -
>>>> https://github.com/scikit-learn/scikit-learn/wiki/GSoC-2015-Proposal:-Multiple-metric-support-for-CV-and-grid_search-and-other-general-improvements
>>>> .
>>>>
>>>> Possible mentors : Andreas Mueller (amueller) and Joel Nothman
>>>> (jnothman)
>>>>
>>>> Any feedback/suggestions/additions/deletions would be awesome. :)
>>>>
>>>> 2. Given that there is a huge interest among students in learning
>>>> about ML, do you think it would be within the scope of/beneficial to skl to
>>>> have all the exercises and/or concepts, from a good quality book (ESL /
>>>> PRML / Murphy) or an academic course like NG's CS229 (not the less rigorous
>>>> coursera version), implemented using sklearn? Or perhaps we could instead
>>>> enhance our tutorials and examples, to be a self study guide to learn about
>>>> ML?
>>>> I have included this in my GSoC proposal but was not quite sure if this
>>>> would be an useful idea!!
>>>>
>>>> Or would it be better if I simply add more examples?
>>>>
>>>> Please let me know your views!!
>>>>
>>>> Thanks
>>>>
>>>>
>>>> R
>>>>
>>>>
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