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[WIP] ENH create callable class to get adequate scorer for a problem #17930

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glemaitre
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closes #17889

Alternative to #17889

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I would like to see a full confusion matrix being reported with this technology, e.g. confusion(A,B). Is that crazy?


estimator = GridSearchCV(
DecisionTreeClassifier(), param_grid={"max_depth": [3, 5]},
scoring=average_precision_scorer,
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I had thought it should be possible to also just pass scoring=scorers. Does this work in the present PR?

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I assume no (I did not remember I had this PR). scorers should be a dict if we want to have multimetric

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Or, after #15126, scorers can be a callable that returns a dict.

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