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Feature importance for random forests #210
When training a random forest, the scikit-learn package returns the feature importances (see http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html), where the feature importance metric is the mean decrease impurity (as described here http://blog.datadive.net/selecting-good-features-part-iii-random-forests/). Can
Looking at the new API proposal #371, this feature will be automatically available.
For example, in the proposed example look at this Line where predictor is created. The predictor contains several methods to save models/metadata and
Also if the predictor implements