Thomas J. Fan

A quick example of doing this without adding a new splitter or function is: ```python from sklearn.model_selection import GridSearchCV from sklearn.ensemble import RandomForestClassifier from sklearn.datasets import make_classification import numpy as...

I have started a integration testing library to start addressing this issue: https://github.com/thomasjpfan/scikit-learn-integration-testing

Makes sense. I am thinking of moving the CI to github actions so I can integrate it into github discussions or issues to ping the maintainers of the upstream projects...

I recall discussing this when developing `permutation_importance` and decided that there was not a use case for selecting a subset. Thank you for providing some use cases! > We want...

I prefer Option 1 over the rest of the options. The only nit is to have the behavior come first: ```python tags.xfail_checks = { "check_estimators_dtypes": ("warn"/"skip"/"raise", "my reason"), } ```...

@adrinjalali I am +1 on passing the `xfail` information directly into `parametrize_with_tests` and `check_estimator` in https://github.com/scikit-learn/scikit-learn/pull/30149.

@coastalwhite Are you okay with the updated PR? It matches the wording from https://github.com/pola-rs/polars/blob/ca6d46cb6746f8da7a71d02c9c00a7e0679a4d02/py-polars/polars/lazyframe/frame.py#L1882-L1884

I see Option 4 as the "proper solution", but I see the following barriers: 1. Community work to get projects on board. 2. There are multiple implementations of OpenMP (depending...

I opened a few PRs to fix the docs, but I am not able to reproduce the `raise JSONDecodeError("Extra data", s, end)` error.

In the long term, I'll want a way to allow `weights_only=True` even if it takes some time to get right with `torch.serialization.add_safe_globals`. For `skorch`, I propose: 1. Use `weights_only=False` as...