I used the the feature selection method: RFE to select feature for features. Now I want to select 20 features(there are about 50 features or more) with LGBM model as following code: But I found that the features(sel.ranking_) are different when the os or os version, or computer is changed. I don't know what caused the changing. More, how to solve it that features selection is fixed. Thanks!
gbm = lgb.LGBMClassifier( boosting_type='gbdt', objective='binary', learning_rate=0.01, colsample_bytree=0.9, subsample=0.8, random_state=21, n_estimators=200, num_leaves=18) sel = RFE(gbm, step=1, n_features_to_select=20, verbose=1) sel.fit(X_train, y_train) print (sel.ranking_)