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[MRG] EHN: Change default n_estimators to 100 for random forest (#11542)
<!-- Thanks for contributing a pull request! Please ensure you have taken a look at the contribution guidelines: https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md#pull-request-checklist --> #### Reference Issues/PRs <!-- Example: Fixes #1234. See also #3456. Please use keywords (e.g., Fixes) to create link to the issues or pull requests you resolved, so that they will automatically be closed when your pull request is merged. See https://github.com/blog/1506-closing-issues-via-pull-requests --> Fixes #11128. #### What does this implement/fix? Explain your changes. Issues deprecation warning message for the default n_estimators parameter for the forest classifiers. Test added for the warning message when the default parameter is used. #### Any other comments? <!-- Please be aware that we are a loose team of volunteers so patience is necessary; assistance handling other issues is very welcome. We value all user contributions, no matter how minor they are. If we are slow to review, either the pull request needs some benchmarking, tinkering, convincing, etc. or more likely the reviewers are simply busy. In either case, we ask for your understanding during the review process. For more information, see our FAQ on this topic: http://scikit-learn.org/dev/faq.html#why-is-my-pull-request-not-getting-any-attention. Thanks for contributing! -->
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Showing with 119 additions and 19 deletions.
- +9 −1 doc/whats_new/v0.20.rst
- +1 −1 examples/applications/plot_prediction_latency.py
- +6 −3 examples/ensemble/plot_ensemble_oob.py
- +4 −2 examples/ensemble/plot_random_forest_regression_multioutput.py
- +1 −1 examples/ensemble/plot_voting_probas.py
- +34 −9 sklearn/ensemble/forest.py
- +34 −0 sklearn/ensemble/tests/test_forest.py
- +14 −0 sklearn/ensemble/tests/test_voting_classifier.py
- +3 −0 sklearn/ensemble/tests/test_weight_boosting.py
- +2 −0 sklearn/feature_selection/tests/test_from_model.py
- +2 −0 sklearn/feature_selection/tests/test_rfe.py
- +2 −1 sklearn/tests/test_calibration.py
- +7 −1 sklearn/utils/estimator_checks.py
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