Xgboost调参总结

from xgboost.sklearn import XGBRegressor
from sklearn.model_selection import ShuffleSplit
import xgboost as xgb

xgb_model_ = XGBRegressor(n_thread=8)
cv_split = ShuffleSplit(n_splits = 6,train_size=0.7,test_size=0.2)
xgb_params={‘max_depth‘:[4,5,6,7],
           ‘learning_rate‘:np.linspace(0.03,0.3,10),
           ‘n_estimators‘:[100,200]}

xgb_search = GridSearchCV(xgb_model_,
                          param_grid=xgb_params,
                          scoring=‘r2‘,
                          iid=False,
                          cv=5)
xgb_search.fit(gbdt_train_data,gbdt_train_label)

print(xgb_search.grid_scores_)
print(xgb_search.best_params_)
print(xgb_search.best_score_)