I am trying to work on feature selection stage for my dataset.
I am a newbie to ML. I have around 60 columns and am trying to select top 15 features. I came to know about RFECV for which I wrote a code like as shown below. I am aware that n_features
is present for RFE
but it is missing for RFECV
. Is there anyother way to assign the number of features to select
?
model = RandomForestClassifier(n_estimators=100, random_state=0)
# create the RFE model and select 15 attributes
rfe = RFECV(model,step=5, cv=5,min_features_to_select = 15,max_features_to_select = 15) # this doesn't work. `n_features=15` also doesn't work
rfe = rfe.fit(X_train_std, y_train)
# summarize the selection of the attributes
feat = rfe.support_
fret = rfe.ranking_
features = X.columns
print(features[feat].tolist())
Can someone help me to get top 15 features only? Where can I configure the n_features
paramter?
Currently it displays more than 30 features. I don't really know how or from where does it get its number (30)?