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Fix generator methods in _DenseAdaBoostClassifier to use yield from instead of return #13

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Jul 4, 2025
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Fix generator methods in _DenseAdaBoostClassifier to use yield from instead of return #13

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8 changes: 4 additions & 4 deletions src/linearboost/linear_boost.py
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Original file line number Diff line number Diff line change
Expand Up @@ -145,7 +145,7 @@ def staged_score(self, X, y, sample_weight=None):
------
z : float
"""
return super().staged_score(X, y, sample_weight)
yield from super().staged_score(X, y, sample_weight)

def staged_predict(self, X):
"""Return staged predictions for X.
Expand All @@ -167,7 +167,7 @@ def staged_predict(self, X):
y : generator of ndarray of shape (n_samples,)
The predicted classes.
"""
return super().staged_predict(X)
yield from super().staged_predict(X)

def staged_decision_function(self, X):
"""Compute decision function of ``X`` for each boosting iteration.
Expand All @@ -190,7 +190,7 @@ def staged_decision_function(self, X):
values closer to -1 or 1 mean more like the first or second
class in ``classes_``, respectively.
"""
return super().staged_decision_function(X)
yield from super().staged_decision_function(X)

def predict_proba(self, X):
"""Predict class probabilities for X.
Expand Down Expand Up @@ -235,7 +235,7 @@ def staged_predict_proba(self, X):
The class probabilities of the input samples. The order of
outputs is the same of that of the :term:`classes_` attribute.
"""
return super().staged_predict_proba(X)
yield from super().staged_predict_proba(X)

def predict_log_proba(self, X):
"""Predict class log-probabilities for X.
Expand Down