Add multi-output support to the bagging module #3449

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arjoly opened this Issue Jul 20, 2014 · 8 comments

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arjoly commented Jul 20, 2014

This would nice to add multi-output support to bagging as in the sklearn.ensemble.forest module. Some code could be refactored.

arjoly changed the title from Add multi-output support to bagging to Add multi-output support to the bagging module Jul 20, 2014

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ldirer commented Jul 20, 2014

I'll try to work on this one.

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arjoly commented Jul 20, 2014

Thanks @ldirer

tliu30 commented Sep 27, 2014

Is this issue still open? If not, I'd like to pick it up!

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ldirer commented Sep 27, 2014

I haven't really worked on it so you are welcome to pick it up if you want!

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arjoly commented Sep 29, 2014

You might want to have a look at the forest code from 0.14 which is similar to what should be done in the multi-output setting.

https://github.com/scikit-learn/scikit-learn/blob/0.14.X/sklearn/ensemble/forest.py

tliu30 commented Sep 30, 2014

Yup! I've been cribbing a good amount from the forest.py code.

I think everything is just about done, but I do have a quick question: is there a notion of a "decision function" in a multi-output setting? I did a quick look and all the estimators implementing a decision_function method seem to only have single-dim outputs.

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arjoly commented Sep 30, 2014

With multi-output data, I would go with a list of arrays. One array for each output.

tliu30 commented Oct 23, 2014

Okay - I've submitted a pull request #3798

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