sklearn.ensemble#
Ensemble-based methods for classification, regression and anomaly detection.
User guide. See the Ensembles: Gradient boosting, random forests, bagging, voting, stacking section for further details.
An AdaBoost classifier. |
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An AdaBoost regressor. |
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A Bagging classifier. |
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A Bagging regressor. |
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An extra-trees classifier. |
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An extra-trees regressor. |
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Gradient Boosting for classification. |
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Gradient Boosting for regression. |
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Histogram-based Gradient Boosting Classification Tree. |
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Histogram-based Gradient Boosting Regression Tree. |
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Isolation Forest Algorithm. |
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A random forest classifier. |
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A random forest regressor. |
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An ensemble of totally random trees. |
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Stack of estimators with a final classifier. |
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Stack of estimators with a final regressor. |
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Soft Voting/Majority Rule classifier for unfitted estimators. |
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Prediction voting regressor for unfitted estimators. |