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@PGijsbers PGijsbers commented Oct 17, 2022

The previous solution had two test conditions (strict and not strict) and several scikit-learn versions, because of two distinct changes within scikit-learn (the removal of min_impurity_split in 1.0, and the restructuring of public/private models in 0.24).
I refactored out the separate test cases to greatly simplify the individual tests, and I added a test case for scikit-learn>=1.0, which was previously not covered.

edit: I think this can now also be more easily parameterized somehow, but I am not sure exactly how to do this when taking into account the skipifs. I would prioritize getting the other tests to green before refactoring further (the main reason I refactored here is because I needed to add cases for >1.0 anyway).

The previous solution had two test conditions (strict and not strict)
and several scikit-learn versions, because of two distinct changes
within scikit-learn (the removal of min_impurity_split in 1.0, and the
restructuring of public/private models in 0.24).
I refactored out the separate test cases to greatly simplify the
individual tests, and I added a test case for scikit-learn>=1.0,
which was previously not covered.
@PGijsbers PGijsbers merged commit 5cd6973 into develop Oct 18, 2022
@PGijsbers PGijsbers deleted the rewrite_reinstantiate_tests branch October 18, 2022 11:09
PGijsbers added a commit to Mirkazemi/openml-python that referenced this pull request Feb 23, 2023
The previous solution had two test conditions (strict and not strict)
and several scikit-learn versions, because of two distinct changes
within scikit-learn (the removal of min_impurity_split in 1.0, and the
restructuring of public/private models in 0.24).
I refactored out the separate test cases to greatly simplify the
individual tests, and I added a test case for scikit-learn>=1.0,
which was previously not covered.
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3 participants