Thanks for your response Fred.
On Jan 24, 2014, at 12:09 AM, Fred Mailhot wrote:
> Is your aim to use this information for feature selection, or do you actually
> want to see which features are being maximally weighted? There's a SO
> question that addresses the latter use:
>
> http://stac
Is your aim to use this information for feature selection, or do you
actually want to see which features are being maximally weighted? There's a
SO question that addresses the latter use:
http://stackoverflow.com/questions/6697/how-to-get-most-informative-features-for-scikit-learn-classifiers
Some classifiers (several of the tree based ones - RandomForest,
GradientBoostingRegressorTree) have a clf.feature_importances_ which can be
plotted to show the relative strength of each feature. sklearn.ensemble
also has a module called partial_dependence, which has a function
plot_partial_depende
Dear all,
I was wondering whether there is a sensitivity analyzer inside scikit-learn? I
saw recursive feature elimination, but I would like to see which features are
the most important for classification in my data.
All the best,
Arman
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