Dear Gilles,
sorry to jump into that discussion, but it raised my interest..
In the R RandomForest package, MeanDecreaseGini can be calculated.
Does scikit-learn somehow scale MeanDecreaseGini to the percentage scale.
Please find attached the variable importance as compute by scikit-learn's
RF
Hi Paul,
sorry to jump into that discussion, but it raised my interest..
> In the R RandomForest package, MeanDecreaseGini can be calculated.
>
>
> Does scikit-learn somehow scale MeanDecreaseGini to the percentage scale.
>
Yes, in randomForest R package there is basically no scaling or
normaliz
Dear Gilles,
sorry to jump into that discussion, but it raised my interest..
In the R RandomForest package, MeanDecreaseGini can be calculated.
Does scikit-learn somehow scale MeanDecreaseGini to the percentage scale.
Please find attached the variable importance as compute by scikit-learn's
RF
Thank you to both of you! I learned something new today :)
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Hi Olivier,
There are indeed several ways to get feature "importances". As often, there
is no strict consensus about what this word means.
In our case, we implement the importance as described in [1] (often cited,
but unfortunately rarely read...). It is sometimes called "gini importance"
or "mea
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
> The variable importance in scikit-learn's implementation of random
> forest is based on the prop
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
