[Scikit-learn-general] weighted kernel density estimation

[Jared Gabor]

I recently modified the kernel density estimation routines in
sklearn/neighbors to include optional weighting of the training samples (to
make analogs to weighted histograms). I'd be interested in contributing
this to scikit-learn, but it's mostly edits of existing code (as opposed to
new source files), and I'm not sure what's the policy in that case.

Here's the code, which could use some more testing and validation (and
documentation):

https://github.com/jaredgabor/scikit-learn/tree/weighted_kde

Thanks for any input,
Jared Gabor

[Joel Nothman]

I think you should submit these changes as a pull request. Thanks, Jared.

Post by Jared Gabor
I recently modified the kernel density estimation routines in
sklearn/neighbors to include optional weighting of the training samples (to
make analogs to weighted histograms). I'd be interested in contributing
this to scikit-learn, but it's mostly edits of existing code (as opposed to
new source files), and I'm not sure what's the policy in that case.
Here's the code, which could use some more testing and validation (and
https://github.com/jaredgabor/scikit-learn/tree/weighted_kde
Thanks for any input,
Jared Gabor
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