It seems the task you are trying to solve is regression: predicting the price. However, you are training a classification model, that assigns a class to every input.

ROC-AUC score is meant for classification problems where the output is the probability of the input belonging to a class. If you do a multi-class classification, then you can compute the score for each class independently.

Moreover, the `predict`

method returns a discrete class, not a probability. Let’s imagine you do a binary classification and have only one example, it should be classified as `False`

. If your classifier yields a probability of 0.7, the ROC-AUC value is 1.0-0.7=0.3. If you use the `predict`

method, the ROC-AUC value will be 1.0-1.0=0.0, which won’t tell you much.