I'm using the random forest classifier (RandomForestClassifier) from scikit-learn on a dataset of two classes (0 and 1). RandomForestClassifier provides directly the importances of the features through the feature_importances_ attribute.
Is features importance in random forest classification depends on classes(0 or 1) of the samples? If I changes the class of data samples (1 and 0), does it effect the features important or they will remain same or it show the features importance of specific class (say 0 or 1)?
I just want to know that the feature importance that comes in RF Classifier are of class 0 or Class 1? Want to check the expressed gene in treatment sample, So the class of the treatment sample should be always 1 and class of the control sample always 0. Is this correct