当我用XGBoostRegressor预测股票价格的,我尝试适应的模式。
# XGBoostRegressor
parameters = {
'n_estimators': [100, 200, 300, 400],
'learning_rate': [0.001, 0.005, 0.01, 0.05],
'max_depth': [8, 10, 12, 15],
'gamma': [0.001, 0.005, 0.01, 0.02],
'random_state': [42]
}
eval_set = [(X_train, y_train), (X_valid, y_valid)]
model = xgb.XGBRegressor(eval_set = eval_set, objective = 'reg:squarederror', verbose = False)
clf = GridSearchCV(model, parameters)
clf.fit(X_train, y_train)
print(f'Best params: {clf.best_params_}')
print(f'Best validation score = {clf.best_score_}')
然后我得到一个警告。
Parameters: { "eval_set", "verbose" } might not be used.
This could be a false alarm, with some parameters getting used by language bindings but
then being mistakenly passed down to XGBoost core, or some parameter actually being used
but getting flagged wrongly here. Please open an issue if you find any such cases.
重复再重复。 我已经改变的参数,但它没有工作。 我没有找到任何方法来解决它吗? 有没有人见面这个问题? 以及如何解决? 谢谢。