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Improve predictions using AdaBoost, RobustBoost, GentleBoost, and more

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To train a classification or regression ensemble, use fitensemble. To build a multiclass model using any of the binary classifier methods GentleBoost, LogitBoost, and RobustBoost, build an ensemble template using templateEnsemble, and then pass it and the training data to fitcecoc.

Functions

fitensemble Fitted ensemble for classification or regression
fitcecoc Fit multiclass models for support vector machines or other classifiers
templateEnsemble Ensemble learning template
predict Predict labels for error-correcting output code multiclass classifiers

Classes

ClassificationEnsemble Ensemble classifier
ClassificationPartitionedEnsemble Cross-validated classification ensemble
CompactClassificationEnsemble Compact classification ensemble class
CompactClassificationECOC Compact multiclass model for support vector machines or other classifiers
ClassificationECOC Multiclass model for support vector machines or other classifiers
ClassificationPartitionedECOC Cross-validated multiclass model for support vector machines or other classifiers
RegressionEnsemble Ensemble regression
RegressionPartitionedEnsemble Cross-validated regression ensemble
CompactRegressionEnsemble Compact regression ensemble class
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