Thanks to visit codestin.com
Credit goes to github.com

Skip to content

[MRG] BUG: enforce row-wise arg max of decision function=predicted class #15504

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
jeremiedbb merged 4 commits into from
Jul 25, 2025
Merged

[MRG] BUG: enforce row-wise arg max of decision function=predicted class #15504

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
05bd8b6
BUG: enforce row-wise arg max of decision function return value is th…
Nov 2, 2019
55145d7
Merge branch 'master' of github.com:scikit-learn/scikit-learn into fi…
Nov 4, 2019
96d2112
Merge remote-tracking branch 'upstream/main' into pr/lakrish/15504
jeremiedbb Jul 25, 2025
20da066
cleanup test & add changelog entry
jeremiedbb Jul 25, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions doc/whats_new/upcoming_changes/sklearn.multiclass/15504.fix.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,3 @@
- Fix tie-breaking behavior in :class:`multiclass.OneVsRestClassifier` to match
`np.argmax` tie-breaking behavior.
By :user:`Lakshmi Krishnan <lakrish>`.
6 changes: 4 additions & 2 deletions sklearn/multiclass.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -499,10 +499,12 @@ def predict(self, X):
maxima = np.empty(n_samples, dtype=float)
maxima.fill(-np.inf)
argmaxima = np.zeros(n_samples, dtype=int)
for i, e in enumerate(self.estimators_):
n_classes = len(self.estimators_)
# Iterate in reverse order to match np.argmax tie-breaking behavior
for i, e in enumerate(reversed(self.estimators_)):
pred = _predict_binary(e, X)
np.maximum(maxima, pred, out=maxima)
argmaxima[maxima == pred] = i
argmaxima[maxima == pred] = n_classes - i - 1
return self.classes_[argmaxima]
else:
thresh = _threshold_for_binary_predict(self.estimators_[0])
Expand Down
19 changes: 19 additions & 0 deletions sklearn/tests/test_multiclass.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,25 @@ def test_check_classification_targets():
check_classification_targets(y)


def test_ovr_ties():
"""Check that ties-breaking matches np.argmax behavior

Non-regression test for issue #14124
"""

class Dummy(BaseEstimator):
def fit(self, X, y):
return self

def decision_function(self, X):
return np.zeros(len(X))

X = np.array([[0], [0], [0], [0]])
y = np.array([0, 1, 2, 3])
clf = OneVsRestClassifier(Dummy()).fit(X, y)
assert_array_equal(clf.predict(X), np.argmax(clf.decision_function(X), axis=1))


def test_ovr_fit_predict():
# A classifier which implements decision_function.
ovr = OneVsRestClassifier(LinearSVC(random_state=0))
Expand Down