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

> If people were interested in putting together a separate package in the > style of the scikit collecting metric learning algorithms with a common API, > I would love to contribute to that too. such ideas should be added to the next sprint wiki page so it can be discussed among the devs A -

Re: [Scikit-learn-general] Metric Learning Algorithms (John Collins)

John, I just meant that if the scikit's maintainers didn't think it was within the scope of the project, I'd still be interested in assembling and contributing to a collection of metric learning algorithms in the scikit's style. -Robert On Apr 21, 2013, at 6:25 PM, John Collins wrote: > Hi Ro

[Scikit-learn-general] Rotations Code?

Hi, Does anyone have any code for computing rotations of components after PCA or FactorAnalysis, etc. E.g., varimax? Thanks, Skipper -- Precog is a next-generation analytics platform capable of advanced analytics on sem

Re: [Scikit-learn-general] Metric Learning Algorithms (John Collins)

Hi Robert, Ken, Robert, I'm not convinced we would need a separate interface. Perhaps I'm wrong because I've not really been exposed to all of the metric learning techniques, but in all the ones I've seen the goal is to learn a matrix A. Calling say .fit(X, y) could create A. Perhaps the response

Re: [Scikit-learn-general] Random patches and coordinates

I think you are right. Moreover, a transformer already exists here . I see two solutions: * The transform() method could return the coordinates and the invers

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

If people were interested in putting together a separate package in the style of the scikit collecting metric learning algorithms with a common API, I would love to contribute to that too. -Robert On Apr 21, 2013, at 3:35 PM, Robert McGibbon wrote: > This would be AWESOME. > > I have code imp

Re: [Scikit-learn-general] Random patches and coordinates

Would a transformer, with an associated inverse_transform, be useful here? It seems to me that it would be the right pattern, however I don't have the code in mind, so I may be wrong. -- Precog is a next-generation analyti

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

This would be AWESOME. I have code implementing Shen, C.; Kim, J.; Wang, L. Scalable large-margin Mahalanobis distance metric learning. IEEE Trans. Neural Networks 2010, 21, 1524–1530, but it yeah, it's not up to sklearn standards either. -Robert On Apr 21, 2013, at 12:49 PM, Kenneth C. Arnol

Re: [Scikit-learn-general] Random patches and coordinates

Hi Alex, Indeed, this solution wouldn't break anything but I generally avoid letting the parameters change the return type of a function. Is this approach used somewhere else in scikit-learn? After the modification of extract_patches_2d, I will probably modify reconstruct_from_patches_2d. I

Re: [Scikit-learn-general] Random patches and coordinates

hi Nicolas, I would add a bool parameter to extract_patches_2d such as return_coordinates. If True it returns (patches, coords) Alex -- Precog is a next-generation analytics platform capable of advanced analytics on semi

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

I have implemented a few metric learning algorithms myself. The quality of that code is nowhere near sklearn standards, but I may have some incentive to improve it soon. -Ken On Sun, Apr 21, 2013 at 3:42 PM, John Collins wrote: > Has anybody or does anybody have plans to implement metric learn

[Scikit-learn-general] Metric Learning Algorithms

Has anybody or does anybody have plans to implement metric learning algorithms like ITML in sklearn? If not, I would like to consider working on this. Thanks, John -- Precog is a next-generation analytics platform capabl

[Scikit-learn-general] Random patches and coordinates

Hi, For an image classification task, I need to extract random patches and their coordinates from images. Until now, I used a custom code to extract them at the same time. I recently tested the extract_patches_2d function from scikit-learn and it seems very fast. To extract the coordinates a