8000 [MRG] BUG Fixes duck typing in voting by thomasjpfan · Pull Request #14287 · scikit-learn/scikit-learn · GitHub
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[MRG] BUG Fixes duck typing in voting #14287

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Merged
merged 5 commits into from
Jul 12, 2019
Merged

[MRG] BUG Fixes duck typing in voting #14287

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1eaeecc
BUG Fixes duck typing in voting
thomasjpfan Jul 7, 2019
ac7268b
TST Fixes test
thomasjpfan Jul 7, 2019
1b40a9f
TST Removes one of the assertions
thomasjpfan Jul 7, 2019
199ac8b
DOC Adds whats new
thomasjpfan Jul 8, 2019
c05d4d3
Merge branch 'master' into fix_duck_typing
qinhanmin2014 Jul 12, 2019
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11 changes: 7 additions & 4 deletions doc/whats_new/v0.22.rst
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Expand Up @@ -69,15 +69,18 @@ Changelog
:mod:`sklearn.ensemble`
.......................

- |Feature| :class:`ensemble.HistGradientBoostingClassifier` and
:class:`ensemble.HistGradientBoostingRegressor` have an additional
parameter called `warm_start` that enables warm starting. :pr:`14012` by
:user:`Johann Faouzi <johannfaouzi>`.

- |Fix| :class:`ensemble.HistGradientBoostingClassifier` and
:class:`ensemble.HistGradientBoostingRegressor` now bin the training and
validation data separately to avoid any data leak. :pr:`13933` by
`Nicolas Hug`_.

- |Feature| :class:`ensemble.HistGradientBoostingClassifier` and
:class:`ensemble.HistGradientBoostingRegressor` have an additional
parameter called `warm_start` that enables warm starting. :pr:`14012` by
:user:`Johann Faouzi <johannfaouzi>`.
- |Fix| :func:`ensemble.VotingClassifier.predict_proba` will no longer be
present when `voting='hard'`. :pr:`14287` by `Thomas Fan`_.

- |Enhancement| :class:`ensemble.HistGradientBoostingClassifier` the training
loss or score is now monitored on a class-wise stratified subsample to
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7 changes: 6 additions & 1 deletion sklearn/ensemble/tests/test_voting.py
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Expand Up @@ -68,7 +68,12 @@ def test_predictproba_hardvoting():
('lr2', LogisticRegression())],
voting='hard')
msg = "predict_proba is not available when voting='hard'"
assert_raise_message(AttributeError, msg, eclf.predict_proba, X)
with pytest.raises(AttributeError, match=msg):
eclf.predict_proba

assert not hasattr(eclf, "predict_proba")
eclf.fit(X, y)
assert not hasattr(eclf, "predict_proba")


def test_notfitted():
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6 changes: 3 additions & 3 deletions sklearn/ensemble/voting.py
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Expand Up @@ -313,9 +313,6 @@ def _collect_probas(self, X):

def _predict_proba(self, X):
"""Predict class probabilities for X in 'soft' voting """
if self.voting == 'hard':
raise AttributeError("predict_proba is not available when"
" voting=%r" % self.voting)
check_is_fitted(self, 'estimators_')
avg = np.average(self._collect_probas(X), axis=0,
weights=self._weights_not_none)
Expand All @@ -335,6 +332,9 @@ def predict_proba(self):
avg : array-like, shape (n_samples, n_classes)
Weighted average probability for each class per sample.
"""
if self.voting == 'hard':
raise AttributeError("predict_proba is not available when"
" voting=%r" % self.voting)
return self._predict_proba

def transform(self, X):
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