1) How to find important features in RandomForest classifier (in sklearn) with high statistical significant?
2) The input data I have is unbalanced which I simply repeat data to compensate that. When I do shuffling, some of these repeated data go to training and some goes to test which definitely increase the prediction accuracy. I know in reality it is not correct but what about if I only want to find important feature?
3) What is the meaning of a feature value (for example, 0.05) in randomforest? in Feature importance it is said that this value means 5% of data is classified correctly by this feature? To find the most important features can I sum up their values till become 0.9 and then I say 90% of data is classified correctly by this features?