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[MRG + 1] Fix _get_importances. #7487

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Merged
merged 1 commit into from
Sep 25, 2016
Merged

[MRG + 1] Fix _get_importances. #7487

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7 changes: 3 additions & 4 deletions sklearn/feature_selection/from_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,17 +14,16 @@

def _get_feature_importances(estimator):
"""Retrieve or aggregate feature importances from estimator"""
if hasattr(estimator, "feature_importances_"):
importances = estimator.feature_importances_
importances = getattr(estimator, "feature_importances_", None)

elif hasattr(estimator, "coef_"):
if importances is None and hasattr(estimator, "coef_"):
if estimator.coef_.ndim == 1:
importances = np.abs(estimator.coef_)

else:
importances = np.sum(np.abs(estimator.coef_), axis=0)

else:
elif importances is None:
raise ValueError(
"The underlying estimator %s has no `coef_` or "
"`feature_importances_` attribute. Either pass a fitted estimator"
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4 changes: 2 additions & 2 deletions sklearn/feature_selection/rfe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -171,9 +171,9 @@ def _fit(self, X, y, step_score=None):
# Get coefs
if hasattr(estimator, 'coef_'):
coefs = estimator.coef_
elif hasattr(estimator, 'feature_importances_'):
coefs = estimator.feature_importances_
else:
coefs = getattr(estimator, 'feature_importances_', None)
if coefs is None:
raise RuntimeError('The classifier does not expose '
'"coef_" or "feature_importances_" '
'attributes')
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