FEA return final cross-validation score in SequentialFeatureSelector #31483
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OmarManzoor
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Jun 10, 2025
doc/whats_new/upcoming_changes/sklearn.feature_selection/31483.feature.rst
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OmarManzoor
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Jun 11, 2025
adrinjalali
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Jun 12, 2025
| final_cv_score_ : float | ||
| The mean cross-validation score of the selected feature set. | ||
| .. versionadded:: 1.6 |
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| .. versionadded:: 1.6 | |
| .. versionadded:: 1.8 |
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| X_new = X[:, self.support_] | ||
| self.final_cv_score_ = cross_val_score( | ||
| cloned_estimator, | ||
| X_new, | ||
| y, | ||
| cv=cv, | ||
| scoring=self.scoring, | ||
| n_jobs=self.n_jobs, | ||
| params=params if _routing_enabled() else None, | ||
| ).mean() |
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This is adding quite a bit of compute time to fit time and the user cannot disable it. Ideally, we should only store things which we can compute as the process normally computes things, and if necessary, have a way to calculate this cv score if the user wants it.
I wouldn't be opposed to adding a method to this class which would run this cv and return the cv results along the mean instead of always computing it.
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Good point. See latest commit. I moved it to a separate method in the class
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