[scikit-learn] SVM-RFE

Andreas Mueller t3kcit at gmail.com
Wed Dec 4 11:12:58 EST 2019

PR welcome ;)

On 12/3/19 11:02 PM, Brown J.B. via scikit-learn wrote:
> 2019年12月3日(火) 5:36 Andreas Mueller <t3kcit at gmail.com 
> <mailto:t3kcit at gmail.com>>:
>     It does provide the ranking of features in the ranking_ attribute
>     and it provides the cross-validation accuracies for all subsets in
>     grid_scores_.
>     It doesn't provide the feature weights for all subsets, but that's
>     something that would be easy to add if it's desired.
> I would guess that there is some population of the user base that 
> would like to track the per-iteration feature weights.
> It would appear to me that a straightforward (un-optimized) 
> implementation would be place a NaN value for a feature once it is 
> eliminated, so that a numpy.ndarray can be returned and immediately 
> dumped to matplotlib.pcolormesh or other visualization routines in 
> various libraries.
> Just an idea.
> J.B.
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