PySpark & MLLib: Random Forest Feature Importances

Question

I\'m trying to extract the feature importances of a random forest object I have trained using PySpark. However, I do not see an example of doing this anywhere in the documen

Answer 1

I believe that this now works. You can call:

from pyspark.ml.classification import RandomForestClassifier
rf = RandomForestClassifier()
model = rf.fit(data)
print model.featureImportances

Running fit on a RandomForestClassifier returns a RandomForestClassificationModel which has the desired featureImportances calculated. I hope that this helps : )