8000 [MRG] Add an example for ensemble.BaggingRegressor by steinfurt · Pull Request #15196 · scikit-learn/scikit-learn · GitHub
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[MRG] Add an example for ensemble.BaggingRegressor #15196

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Merged
merged 3 commits into from
Oct 21, 2019
Merged

[MRG] Add an example for ensemble.BaggingRegressor #15196

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f83f2a5
Add example for ensemble.BaggingRegressor
steinfurt Oct 12, 2019
01c11b9
Increase speed of ensemble.BaggingClassifier
steinfurt Oct 12, 2019
157b730
Implement just one example and relax accuracy
steinfurt Oct 18, 2019
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20 changes: 15 additions & 5 deletions sklearn/ensemble/_bagging.py
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Original file line number Diff line number Diff line change
Expand Up @@ -546,14 +546,11 @@ class BaggingClassifier(ClassifierMixin, BaseBagging):
>>> from sklearn.svm import SVC
>>> from sklearn.ensemble import BaggingClassifier
>>> from sklearn.datasets import make_classification
>>> X, y = make_classification(n_samples=1000, n_features=4,
>>> X, y = make_classification(n_samples=100, n_features=4,
... n_informative=2, n_redundant=0,
... random_state=0, shuffle=False)
>>> clf = BaggingClassifier(n_estimators=100, random_state=0).fit(X, y)
>>> clf.predict([[0, 0, 0, 0]])
array([1])
>>> clf = BaggingClassifier(base_estimator=SVC(),
... n_estimators=100, random_state=0).fit(X, y)
... n_estimators=10, random_state=0).fit(X, y)
>>> clf.predict([[0, 0, 0, 0]])
array([1])

Expand Down Expand Up @@ -935,6 +932,19 @@ class BaggingRegressor(RegressorMixin, BaseBagging):
`oob_prediction_` might contain NaN. This attribute exists only
when ``oob_score`` is True.

Examples
--------
>>> from sklearn.svm import SVR
>>> from sklearn.ensemble import BaggingRegressor
>>> from sklearn.datasets import make_regression
>>> X, y = make_regression(n_samples=100, n_features=4,
... n_informative=2, n_targets=1,
... random_state=0, shuffle=False)
>>> regr = BaggingRegressor(base_estimator=SVR(),
... n_estimators=10, random_state=0).fit(X, y)
>>> regr.predict([[0, 0, 0, 0]])
array([-2.8720...])

References
----------

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0