Re: [Scikit-learn-general] [GSoC] Metric Learning

Neighborhood Component Analysis is more cited than ITML. On Wed, Mar 18, 2015 at 11:39 PM, Artem wrote: > Hello everyone > > Recently I mentioned metric learning as one of possible projects for this > years' GSoC, and would like to hear your comments. > > Metric learning, as follows from the nam

Re: [Scikit-learn-general] update liblinear

oh thanks On Thu, Mar 19, 2015 at 3:20 PM, Joel Nothman wrote: > I should have replied here. Liblinear with sample weights: > https://github.com/scikit-learn/scikit-learn/pull/2784 > > On 20 March 2015 at 09:12, Charles Martin wrote: >> >> Yes and thanks >> >> Sent from my iPhone >> >> > On Mar

Re: [Scikit-learn-general] update liblinear

I should have replied here. Liblinear with sample weights: https://github.com/scikit-learn/scikit-learn/pull/2784 On 20 March 2015 at 09:12, Charles Martin wrote: > Yes and thanks > > Sent from my iPhone > > > On Mar 19, 2015, at 2:36 PM, Andreas Mueller wrote: > > > > Hi Charles. > > That is u

Re: [Scikit-learn-general] GSoC2015 Hyperparameter Optimization topic

This is off-topic, but I should note that there is a patch at https://github.com/scikit-learn/scikit-learn/pull/2784 awaiting review for a while now... On 20 March 2015 at 08:16, Charles Martin wrote: > I would like to propose extending the linearSVC package > by replacing the liblinear version

Re: [Scikit-learn-general] update liblinear

Yes and thanks Sent from my iPhone > On Mar 19, 2015, at 2:36 PM, Andreas Mueller wrote: > > Hi Charles. > That is unrelated to the GSoC mail you responded to, right? > > I think updating liblinear sound like a good idea, if it doesn't end up > being to complicated. > Allowing instance weigh

Re: [Scikit-learn-general] GSoC2015 Hyperparameter Optimization topic

> Does anybody know of further optimization approaches that were not > mentioned below and that we could consider? Maybe parallel computing. A grid search is an embarrassingly parallel problem. A Bayesian optimization is not. We have the necessary framework only to tackle embarrassingly parallel

Re: [Scikit-learn-general] update liblinear

Hi Charles. That is unrelated to the GSoC mail you responded to, right? I think updating liblinear sound like a good idea, if it doesn't end up being to complicated. Allowing instance weights is certainly something we'd like to have. You should check how far our code diverged, but I think for lib

Re: [Scikit-learn-general] GSoC2015 Hyperparameter Optimization topic

Hi All, you can find my proposal for the hyperparameter optimization topic here: * http://goo.gl/XHuav8 * https://docs.google.com/document/d/1bAWdiu6hZ6-FhSOlhgH-7x3weTluxRfouw9op9bHBxs/edit?usp=sharing Please give feedback! Cheers, Christof On 20150310 15:27, Sturla Molden wrote: > Andreas M

Re: [Scikit-learn-general] GSoC2015 Hyperparameter Optimization topic

I would like to propose extending the linearSVC package by replacing the liblinear version with a newer version that 1. allows setting instance weights 2. provides the dual variables /Lagrange multipliers This would facilitate research and development of transductive SVMs and related semi-supervi

Re: [Scikit-learn-general] [GSoC] Metric Learning

Yes, your suggestion is viable, but I have not seen any algorithms in sklearn that use y like that in fit method. ​​ > I would have thought in the case of Mahalanobis distances that transform > would transform each feature such that the resulting feature space was > Euclidean. ​Exactly. Thus, met

[Scikit-learn-general] Student looking to contribute toward scikit-learn

Hello everyone, I am a final year student of Computer Science from India. I study at the "Vishwakarma Institute of Technology" in Pune. I am interested in various areas under Machine Learning and Aritificial Intelligence. I have a theoretical background in both these subjects and a limited experie