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. | |
| An AdaBoost regressor. | |
| A Bagging classifier. | |
| A Bagging regressor. | |
| An extra-trees classifier. | |
| An extra-trees regressor. | |
| Gradient Boosting for classification. | |
| Gradient Boosting for regression. | |
| Histogram-based Gradient Boosting Classification Tree. | |
| Histogram-based Gradient Boosting Regression Tree. | |
| Isolation Forest Algorithm. | |
| A random forest classifier. | |
| A random forest regressor. | |
| An ensemble of totally random trees. | |
| Stack of estimators with a final classifier. | |
| Stack of estimators with a final regressor. | |
| Soft Voting/Majority Rule classifier for unfitted estimators. | |
| Prediction voting regressor for unfitted estimators. |