xgboost的“适合”功能是否允许继续训练？

Question

我想知道我的K-Fold实现是否正确：

from sklearn.model_selection import KFold

kf = KFold(n_splits=numFolds, shuffle=False, random_state=7)
sales_prediction_model = xgb.XGBRegressor(
                    silent=False,
                    learning_rate=0.03,
                    n_estimators=10000,
                    max_depth=4,
                    # sub_sample=0.8,
                    gamma=1,
                    colsample_bytree=0.8,
                    n_jobs=30
                )

for train_index, test_index in kf.split(X_train):
     X_tr, X_te = X_train.iloc[train_index], X_train.iloc[test_index]
     y_tr, y_te = y_train.iloc[train_index], y_train.iloc[test_index]
     eval_set = [(X_tr, y_tr), (X_te, y_te)]
     sales_prediction_model.fit(X_tr, y_tr, verbose=False,
          early_stopping_rounds=15,eval_set=eval_set, eval_metric="mae")

健身功能是继续训练还是从头开始？

感谢您的帮助。

（xgboost文档仅说明：“ Fit梯度增强模型” ）