Classification metrics can't handle a mix of multiclass and continuous targets

This error message usually occurs when you try to use a classification metric, such as accuracy or F1 score, on a target variable that contains both categorical and continuous values.

Classification metrics are designed to evaluate how well a model performs on categorical targets, such as predicting the correct label for an image or classifying an email as spam or not spam. They cannot be used to evaluate models that predict continuous values, such as predicting the price of a house or the amount of rainfall in a given area.

To resolve this error, you need to ensure that your target variable is either entirely categorical or entirely continuous. If you have a mix of categorical and continuous variables, you may need to use different evaluation metrics for each variable type or consider transforming the continuous variable into a categorical variable using binning or other techniques.