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
<mailto: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 <mailto: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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