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fix: MultiOutputClassifier exposes classes_ (swev-id: scikit-learn__scikit-learn-14629)#44

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casey-brooks wants to merge 2 commits intoscikit-learn__scikit-learn-14629from
fix/multioutput-classes-cross-val-predict
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fix: MultiOutputClassifier exposes classes_ (swev-id: scikit-learn__scikit-learn-14629)#44
casey-brooks wants to merge 2 commits intoscikit-learn__scikit-learn-14629from
fix/multioutput-classes-cross-val-predict

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@casey-brooks casey-brooks commented Dec 26, 2025

Summary

  • add wrapper-level classes_ to MultiOutputClassifier and refresh it during partial_fit
  • document classes_ and add regression coverage for cross_val_predict with MultiOutputClassifier
  • ensure ClassifierChain order validation keeps expected indentation

Testing

  • . /workspace/sklearn-py37/bin/activate && PYTHONPATH=. pytest sklearn/model_selection/tests/test_validation.py -k multioutput -vv
  • . /workspace/sklearn-py37/bin/activate && flake8 --ignore=E121,E123,E126,E24,E704,W503,W504,E731,E303 sklearn/multioutput.py sklearn/model_selection/tests/test_validation.py
  • . /workspace/sklearn-py37/bin/activate && PYTHONPATH=. python - <<'PY'
    from sklearn.datasets import make_multilabel_classification
    from sklearn.multioutput import MultiOutputClassifier
    from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
    from sklearn.model_selection import cross_val_predict
    X, Y = make_multilabel_classification(random_state=0)
    mo_lda = MultiOutputClassifier(LinearDiscriminantAnalysis())
    cross_val_predict(mo_lda, X, Y, cv=5, method='predict_proba')
    PY

Failure stack trace (before fix)

Traceback (most recent call last):
  File "<stdin>", line 9, in <module>
  File "/workspace/scikit-learn/sklearn/model_selection/_validation.py", line 766, in cross_val_predict
    for train, test in cv.split(X, y, groups))
  File "/workspace/sklearn-py37/lib/python3.7/site-packages/joblib/parallel.py", line 1029, in __call__
    if self.dispatch_one_batch(iterator):
  File "/workspace/sklearn-py37/lib/python3.7/site-packages/joblib/parallel.py", line 847, in dispatch_one_batch
    self._dispatch(tasks)
  File "/workspace/sklearn-py37/lib/python3.7/site-packages/joblib/parallel.py", line 765, in _dispatch
    job = self._backend.apply_async(batch, callback=cb)
  File "/workspace/sklearn-py37/lib/python3.7/site-packages/joblib/_parallel_backends.py", line 208, in apply_async
    result = ImmediateResult(func)
  File "/workspace/sklearn-py37/lib/python3.7/site-packages/joblib/_parallel_backends.py", line 572, in __init__
    self.results = batch()
  File "/workspace/sklearn-py37/lib/python3.7/site-packages/joblib/parallel.py", line 253, in __call__
    for func, args, kwargs in self.items]
  File "/workspace/sklearn-py37/lib/python3.7/site-packages/joblib/parallel.py", line 253, in <listcomp>
    for func, args, kwargs in self.items]
  File "/workspace/scikit-learn/sklearn/model_selection/_validation.py", line 861, in _fit_and_predict
    for i_label in range(len(predictions))]
  File "/workspace/scikit-learn/sklearn/model_selection/_validation.py", line 861, in <listcomp>
    for i_label in range(len(predictions))]
AttributeError: 'MultiOutputClassifier' object has no attribute 'classes_'

Fixes #42

@casey-brooks casey-brooks requested a review from a team December 26, 2025 03:35
@casey-brooks
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casey-brooks commented Dec 26, 2025

Test & Lint Summary

  • . /workspace/sklearn-py37/bin/activate && PYTHONPATH=. pytest sklearn/model_selection/tests/test_validation.py -k multioutput -vv
    → 3 passed, 57 deselected
  • . /workspace/sklearn-py37/bin/activate && flake8 --ignore=E121,E123,E126,E24,E704,W503,W504,E731,E303 sklearn/multioutput.py sklearn/model_selection/tests/test_validation.py
    → no issues
  • . /workspace/sklearn-py37/bin/activate && PYTHONPATH=. python - <<'PY'
    from sklearn.datasets import make_multilabel_classification
    from sklearn.multioutput import MultiOutputClassifier
    from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
    from sklearn.model_selection import cross_val_predict
    X, Y = make_multilabel_classification(random_state=0)
    mo_lda = MultiOutputClassifier(LinearDiscriminantAnalysis())
    pred_proba = cross_val_predict(mo_lda, X, Y, cv=5, method='predict_proba')
    print(len(pred_proba))
    print([arr.shape for arr in pred_proba])
    PY
    → prints and

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casey-brooks commented Dec 26, 2025

Repro script output: 5 and [(100, 2), (100, 2), (100, 2), (100, 2), (100, 2)]

noa-lucent
noa-lucent requested changes Dec 26, 2025
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Thanks for tackling the MultiOutputClassifier regression and adding coverage. One existing regression guard () lost its assertion on the 3D-input smoke test; please reinstate the check so we keep that protection in place.

noa-lucent
noa-lucent approved these changes Dec 26, 2025
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Looks good—thanks for restoring the 3D-input assertion and for the overall fix. The tests and MultiOutputClassifier updates resolve the issue on my side.

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@casey-brooks @noa-lucent