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FIX CalibratedClassifierCV with string targets #28843

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Merged
merged 3 commits into from
Apr 16, 2024
Merged

FIX CalibratedClassifierCV with string targets #28843

merged 3 commits into from
Apr 16, 2024

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jeremiedbb
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@jeremiedbb jeremiedbb commented Apr 15, 2024 •
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Fixes #28841

By removing _validate_data, #19555 introduced a regression in CalibratedClassifierCV. This is due to how numpy behaves with element-wise comparison of arrays of strings.

y = ["1", "1", "2", "2"]
c = np.array(["1", "2"])

# before, y was validated, hence was an array
np.array(y) == c[0]
# array([ True,  True, False, False])

# now, y is not validated, hence still a list
y == c[0]
# False

Surprisingly, the second one works with integers.

Using np.unique will work no matter what to count the number of occurrences.

@jeremiedbb jeremiedbb added this to the 1.5 milestone Apr 15, 2024
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github-actions bot commented Apr 15, 2024 •
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✔️ Linting Passed

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@jeremiedbb jeremiedbb mentioned this pull request Apr 15, 2024
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jeremiedbb
jeremiedbb commented Apr 15, 2024
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doc/whats_new/v1.5.rst Outdated Show resolved Hide resolved
@adrinjalali
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cc @OmarManzoor @Charlie-XIAO maybe?

OmarManzoor
OmarManzoor approved these changes Apr 16, 2024
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LGTM. Thanks @jeremiedbb

@OmarManzoor OmarManzoor merged commit 481b457 into scikit-learn:main Apr 16, 2024
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@adrinjalali adrinjalali adrinjalali approved these changes

@OmarManzoor OmarManzoor OmarManzoor approved these changes

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Version 1.0 breaks cross-validation with string targets
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@jeremiedbb @adrinjalali @OmarManzoor
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