I have 9 parameters, I want to select 6 important parameters and discard 3. What is the best method to do it? I have seen some methods of ranking the parameters by recursive feature elimination (e.g. RFECV). Can I use the random forest classification to rank the parameters and select those important parameters and use them for the random forest classifier? My question is that while using a random forest algorithm for feature selection, how can I make sure that I have used the best hyperparameters. Is it right to use an un-hyper tuned random forest classifier and decide the importance of the parameter? Are there any other methods for selecting important features?
Selecting important features to perform random forest classification
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