I have a Pandas dataframe X(20346, 4116). All independent columns have binary variable as 0 or 1. Whereas dependent column has continuous variable. When I execute below code using the scikit-learn library, it takes for ever and I am not getting any result.X_train, X_test, y_train, y_test = train_test_split(X13, y, train_size=0.8)rf = RandomForestRegressor(n_estimators=100,  max_features='auto', oob_score=True,                            n_jobs=1, verbose=0)rf.fit(X_train, y_train) I am using this for feature selection. In case of less number of rows I can get result. But when number of rows go up then this problem starts happening. Do you have any idea how to make it work?
Scikit Learn's RandomForestRegressor is not giving results on large data set
python;random forest;scikit learn