I was trying to select the most important features of a data set using Boruta in python. I have split the data into training and test set. Then I used SVM regressor to fit the data. Then I used Boruta to measure feature importance.The code is as follows:
from sklearn.svm import SVR svclassifier = SVR(kernel='rbf',C=1e4, gamma=0.1) svm_model= svclassifier.fit(x_train, y_train) from boruta import BorutaPy feat_selector = BorutaPy(svclassifier, n_estimators='auto', verbose=2, random_state=1) feat_selector.fit(x_train, y_train) feat_selector.support_ feat_selector.ranking_ X_filtered = feat_selector.transform(x_train)
But I get this error
What might be causing this error?
Does Boruta work with any kind of models? i.e linear models, tree-based models, neural nets, etc.?