import os os.environ['KMP_DUPLICATE_LIB_OK']='True' from xgboost import XGBRegressor

best_params = {'learning_rate': 0.16, 'n_estimators': 100,
               'max_depth': 6, 'min_child_weight': 7,
               'subsample': 0.9, 'colsample_bytree': 0.7, 'nthread': -1,
               'scale_pos_weight': 1, 'random_state': 42,

               #next parameters are used to enable gpu for fasting fitting
               'tree_method': 'gpu_hist', 'max_bin': 16,
               'gpu_id': 0
              }

xgb_model = XGBRegressor(
        **best_params)

xgb_model.fit(
        cur_train_x,
        cur_train_y,
        eval_metric="rmse",
        eval_set=[(cur_train_x, cur_train_y)],
        verbose=True,
        early_stopping_rounds = 10)