Im doing a model with XGBRegressor with multiple outputs:
from xgboost import XGBRegressor
from sklearn.multioutput import MultiOutputRegressor
XBC = XGBRegressor(booster = 'gbtree',learning_rate =0.01,
n_estimators=5000,early_stopping_rounds=50,
evals= [X_test,Y_test],max_depth=5,gamma=0.1,eval_metric="rmse")
classifier_XBC = MultiOutputRegressor(XBC)
classifier_XBC.fit(X_train, Y_train)
WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:573: Parameters: { "early_stopping_rounds", "evals" } might not be used.
This may not be accurate due to some parameters are only used in language bindings but passed down to XGBoost core. Or some parameters are not used but slip through this verification. Please open an issue if you find above cases.
My code is outputting the warning above, however, it is running with no errors. I checked all the parameters in the xgboost documentation. What does it means? Has anyone had this issue before??
