FIX Support extra class_weights in compute_class_weight #22595
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I find the behaviour a bit dangerous because you could potentially accept a key with a typo that will not be used. |
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I updated the PR to be more strict when it comes to unweighted classes:
This means that an error is raised: from sklearn.tree import DecisionTreeClassifier
tree = DecisionTreeClassifier(class_weight={"dogs": 2, "cat": 1})
# Raises error
tree.fit([[1, 2, 3], [1, 3, 2]], ["dog", "cat"])
# ValueError: The classes, ['dog'], are not in class_weight |
glemaitre
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Mar 3, 2022
jjerphan
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Mar 4, 2022
Diwakar-Gupta
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Mar 7, 2022
thomasjpfan
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Mar 8, 2022
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Reference Issues/PRs
Fixes #22413
What does this implement/fix? Explain your changes.
This PR:
compute_class_weightto allowclass_weightto contain other classes that is not in theclasses.class_weightappear inclasses, then an error is raised.Any other comments?
I think the intention of using
class_weightsas the source of truth is to prevent this type of error:with this PR,
"dog"would not be weighted.