Traceback (most recent call last): File "C:\Users\dell\OneDrive\code\随机森林模拟.py", line 12, in <module> y_pred = model.predict(X) File "C:\Users\dell\AppData\Roaming\Python\Python37\site-packages\sklearn\ensemble\_forest.py", line 969, in predict check_is_fitted(self) File "C:\Users\dell\AppData\Roaming\Python\Python37\site-packages\sklearn\utils\validation.py", line 1222, in check_is_fitted raise NotFittedError(msg % {"name": type(estimator).__name__}) sklearn.exceptions.NotFittedError: This RandomForestRegressor instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.
时间: 2023-07-06 09:29:06 浏览: 107
这个错误是因为你在使用随机森林模型的 predict 函数之前没有先对模型进行训练拟合(fit)操作。在使用 predict 函数之前需要先调用 fit 函数对模型进行训练,使其能够对新的数据进行预测。你需要先调用 fit 函数,例如 `model.fit(X_train, y_train)`,然后再使用 predict 函数进行预测。
相关问题
Traceback (most recent call last): File "C:\Users\dell\OneDrive\code\随机森林模拟.py", line 9, in <module> X = X[model.feature_names_in_] AttributeError: 'RandomForestRegressor' object has no attribute 'feature_names_in_'
这个错误可能是因为您在使用 `RandomForestRegressor` 模型时,没有为其指定特征名称。您可以尝试在训练模型时指定特征名称,例如:
```
model = RandomForestRegressor()
model.fit(X_train, y_train, feature_names=['feature1', 'feature2', ...])
```
或者您可以检查您的代码,确保在使用 `model.feature_names_in_` 之前,已经定义了 `model` 并且 `feature_names_in_` 属性存在。
Traceback (most recent call last): File "C:\Users\admin\Documents\WeChat Files\wxid_2pmuyu7hto9n22\FileStorage\File\2023-07\code\code\789.py", line 1, in <module> import clickhouse_driver File "D:\anaconda\Lib\site-packages\clickhouse_driver\__ini
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