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[ENH] Adds a check for consistent output for predict and predict_proba #2824

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[ENH] Adds a check for consistent output for predict and predict_proba #2824

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5cb99b7
enh: adds a check for consistent output for predict and predict_proba
notaryanramani May 19, 2025
ca80c18
using classes_ to obtain predictions labels
notaryanramani May 22, 2025
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7 changes: 7 additions & 0 deletions aeon/testing/estimator_checking/_yield_classification_checks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -374,3 +374,10 @@ def check_classifier_output(estimator, datatype):
# check predict proba (all classifiers have predict_proba by default)
y_proba = estimator.predict_proba(FULL_TEST_DATA_DICT[datatype]["test"][0])
_assert_predict_probabilities(y_proba, datatype, n_classes=len(unique_labels))

y_pred_proba = np.argmax(y_proba, axis=1)
_assert_predict_labels(y_pred_proba, datatype, unique_labels=unique_labels)
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is line 379 necessary?

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I just added it as we were checking the y_pred and y_proba. But since we get y_pred_proba from y_proba, I don't think it is necessary.


np.testing.assert_array_equal(
y_pred, y_pred_proba, err_msg="predict and predict_proba are not consistent"
)
9 changes: 9 additions & 0 deletions aeon/testing/estimator_checking/_yield_clustering_checks.py
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Expand Up @@ -141,6 +141,15 @@ def check_clusterer_output(estimator, datatype):
assert isinstance(y_proba, np.ndarray)
np.testing.assert_almost_equal(y_proba.sum(axis=1), 1, decimal=4)

# check predict and predict_proba have consistent outputs
y_pred_proba = np.argmax(y_proba, axis=1)

np.testing.assert_array_equal(
y_pred,
y_pred_proba,
err_msg="predict and predict_proba outputs are inconsistent",
)


def check_clusterer_saving_loading_deep_learning(estimator_class, datatype):
"""Test Deep Clusterer saving."""
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