XGB分类器错误无效类从'y”的唯一值推断出

Question

这是我在这里的第一个问题。我已经培训了一个XGB分类器，并且在本地上运行良好，但是我在Google Cloud Virtual Machine上的Jupyter笔记本中尝试了同样的方法，并且会出现错误。

我的代码：

`param_grid = {"max_depth": [3, None],
              "max_features": [20, 30, 40],
              "min_samples_split": [2, 3, 10],
              "bootstrap": [True, False],
              "error_score": ["raise"],
              "criterion": ["gini", "entropy"]}
xclas = XGBClassifier() 
grid = GridSearchCV(estimator=xclas, param_grid=param_grid, cv=5 )
grid.fit(X_res1, y_res1)`

错误输出：

    Traceback (most recent call last):
  File "/opt/conda/lib/python3.7/site-packages/sklearn/model_selection/_validation.py", line 680, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File "/opt/conda/lib/python3.7/site-packages/xgboost/core.py", line 532, in inner_f
    return f(**kwargs)
  File "/opt/conda/lib/python3.7/site-packages/xgboost/sklearn.py", line 1358, in fit
    f"Invalid classes inferred from unique values of `y`.  "
ValueError: Invalid classes inferred from unique values of `y`.  Expected: [0 1 2 3 4 5 6 7 8], got [1 2 3 4 5 6 7 8 9]

我已经读到当“ y”不是int类型时可能会发生此问题，但是我已经检查了，并且是int。有什么办法可以解决这个问题吗？