sklearn GridSearchCV not using sample_weight in score function

Question

I have data with differing weights for each sample. In my application, it is important that these weights are accounted for in estimating the model and comparing alternative

Answer 1

Just pointing out that there is an ongoing effort to support this important feature: https://github.com/scikit-learn/scikit-learn/pull/13432

But it seems that because of backward compatibility issues and the desire to tackle the more general problem of passing arbitrary sample related information it is taking a bit too long. The last attempt seems to be: https://github.com/scikit-learn/scikit-learn/pull/16079

Here is a good review of the issue: http://deaktator.github.io/2019/03/10/the-error-in-the-comparator/