All the 8 fits failed. It is very likely that your model is misconfigured. You can try to debug the error by setting error_score='raise'.

This error message suggests that there is a problem with the configuration of your model and that all 8 fits have failed. One possible solution is to set the error_score parameter to 'raise', which will raise an exception if there is an error during the fitting process. This can help you identify the specific issue that is causing the problem.

However, it's difficult to provide more specific advice without more information about the specific model and code you are using. If you can provide more context or details about your project, I may be able to provide more guidance.

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All the 150 fits failed. It is very likely that your model is misconfigured. You can try to debug the error by setting error_score='raise'.

这个错误通常是由于模型配置错误或者训练数据集问题导致的。你可以尝试设置`error_score='raise'`来调试错误，这样就可以在发生错误时抛出异常，方便调试。另外，你也可以检查一下模型的参数和超参数是否正确，是否需要进行调整。如果仍然有问题，你可以提供更多的代码和错误信息，我会尽力帮助你解决问题。

All the 100 fits failed. It is very likely that your model is misconfigured. You can try to debug the error by setting error_score='raise'.

This error message indicates that all 100 fits of your model have failed, and suggests that there may be an issue with the configuration of your model. One suggestion is to set the error_score parameter to 'raise' when calling the fit method, which will raise an exception when an error occurs during training. This can help you identify the specific error that is causing the fits to fail, and then you can take steps to address that error. Additionally, you may want to review your model's hyperparameters and make sure they are appropriate for your data and task.