Sorry for the late reply, my internet connection failed me. I've seen only
cross validation being the problem for semi-supervised learning, on the
issue tracker. Would someone else like to discuss about this?
So, should I scrap the self-taught learning algorithm from the proposal?
Also, I'm looking into transductive SVMs.
Vinayak
On Thu, Mar 26, 2015 at 2:41 AM, Andreas Mueller <t3k...@gmail.com> wrote:
> Sorry for the confusion, but that was actually not the meta-estimator I
> was thinking of.
> I was thinking about the iterative self-learning method, which is a
> classical way to make a supervised algorithm semi-supervised.
> Either way, these would be quite simple meta-estimators, and wouldn't
> require any new algorithms.
> [What you explained in your proposal is basically
>
> LinearSVC().fit(DictionaryLearning().fit(X_unlabeled).transform(X_train),
> y_train)]
>
> Therefore I think they are not enough meat for a whole GSoC.
> Are there other infrastructure things that need to change for
> semi-supervised learning to become a first-class citizen in sklearn?
> If not, maybe it would be worth adding another algorithm, such as
> transductive SVMs?
>
> Best,
> Andy
>
>
>
>
> On 03/25/2015 04:12 PM, Vinayak Mehta wrote:
>
> What do you think about the proposal though?
>
> Vinayak
>
> On Thu, Mar 26, 2015 at 1:39 AM, Andreas Mueller <t3k...@gmail.com> wrote:
>
>> Hi Vinayak.
>> I was specifically commenting about the self-taught clustering paper that
>> you mentioned in your email.
>> Sorry about not being specific.
>>
>> Best,
>> Andy
>>
>>
>>
>> On 03/25/2015 04:01 PM, Vinayak Mehta wrote:
>>
>> Hi Andy
>>
>> The idea wiki showed issue #1243 as a reference link which specifically
>> mentions self-taught learning as a solution for turning an estimator into a
>> semi-supervised one. So, I tried to base my proposal on that. Could you
>> guide me on how to focus more on semi-supervised learning than transfer
>> learning by commenting on specific places in the doc. :) And maybe provide
>> some points on where I can improve it as it is somewhat abstract right now
>> I think.
>>
>> Thanks,
>> Vinayak
>>
>> On Thu, Mar 26, 2015 at 1:05 AM, Andreas Mueller <t3k...@gmail.com>
>> wrote:
>>
>>> Hi Vinayak.
>>> That looks more like a transfer-learning task and I'm not sure how that
>>> a) tie into the project b) work with the sklearn API.
>>> So I'd be -1 on that.
>>>
>>> Cheers,
>>> Andy
>>>
>>>
>>>
>>> On 03/25/2015 04:16 AM, Vinayak Mehta wrote:
>>>
>>> Hi everyone!
>>>
>>> I've added my proposal to the wiki page. Please suggest improvements.
>>> Here is a link to the Google doc:
>>> https://docs.google.com/document/d/1JCbeakBtPTpfis2grw00I8Y1VVivssAdiHlm1ejS3E8/edit?usp=sharing
>>>
>>> Further, I want to discuss on if this ->
>>> http://www.machinelearning.org/archive/icml2008/papers/432.pdf could be
>>> added to my proposal.
>>>
>>> Thanks,
>>> Vinayak
>>>
>>>
>>>
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