DOC add BaggingClassifier Examples #14923
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I honestly don't understand why the classifier output for the Doctest fails in the azure pipeline. I could use some clarification on those. |
adrinjalali
reviewed
Sep 8, 2019
Azure Pipeline partially breaks on the pprint Left the response in as a comment, I think they make the use a bit clearer
Co-Authored-By: Adrin Jalali <adrin.jalali@gmail.com>
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Thank you for your help @adrinjalali |
adrinjalali
approved these changes
Oct 4, 2019
sklearn/ensemble/bagging.py
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| ... n_informative=2, n_redundant=0, | ||
| ... random_state=0, shuffle=False) | ||
| >>> clf = BaggingClassifier(n_estimators=100, random_state=0).fit(X, y) | ||
| >>> print(clf.predict([[0, 0, 0, 0]])) |
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You don't need to print, you would see the output in the REPL anyway.
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I know, I just followed the suggestion from your last review. Should I revert this?
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I thought my suggestion was to remove it :P
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Ha. I got confused, sorry about that.
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Tests failing because when you remove the print, the output becomes |
adrinjalali
approved these changes
Oct 6, 2019
sklearn/ensemble/bagging.py
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| @@ -541,6 +541,23 @@ class BaggingClassifier(ClassifierMixin, BaseBagging): | |||
| `oob_decision_function_` might contain NaN. This attribute exists | |||
| only when ``oob_score`` is True. | |||
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Toward #3846
this PR adds an example to
ensemble.BaggingClassifierping @adrinjalali