Hey @markdregan

Here a PR to expand the fit method of Shuffle features to accommodate sample weights.

This is training the model with sample weights. The predictions done after shuffling are done without weighting. This is, based on my understanding, the correct procedure. Correct me if I am wrong.

Thank you!

Looking at the cross_validate logic, the performance on test set is calculated without sample_weights:

https://github.com/scikit-learn/scikit-learn/blob/364c77e047ca08a95862becf40a04fe9d4cd2c98/sklearn/model_selection/_validation.py#L707-L711

Sample weights is used only to train:

https://github.com/scikit-learn/scikit-learn/blob/364c77e047ca08a95862becf40a04fe9d4cd2c98/sklearn/model_selection/_validation.py#L682-L686

Thank you! I will test this week. 🙌

TY. Confirmed working correctly. Thanks for the fast PR!