I posted a brief description of the algorithm. The method that we implement
is briefly described in ESLII. Gilles is the expert here, he can give more
details on the issue.
2013/4/4 Olivier Grisel <[email protected]>
> The variable importance in scikit-learn's implementation of random
> forest is based on the proportion of samples that were classified by
> the feature at some point in one of the decision trees evaluation.
>
>
> http://scikit-learn.org/stable/modules/ensemble.html#feature-importance-evaluation
>
> This method seems different from the OOB based method of Breiman 2001
> (section 10):
>
> http://www.stat.berkeley.edu/~breiman/randomforest2001.pdf
>
> Is there any reference for the method implemented in the scikit?
>
> Here is the original Stack Overflow question:
>
>
> http://stackoverflow.com/questions/15810339/how-are-feature-importances-in-randomforestclassifier-determined/15811003?noredirect=1#comment22487062_15811003
>
> --
> Olivier
> http://twitter.com/ogrisel - http://github.com/ogrisel
>
>
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