Documentation

Boosting

Improve predictions using AdaBoost, RobustBoost, GentleBoost, and more

To train an ensemble of boosted classification trees, or to explore other ensemble-learning options, use the Classification Learner App.

For greater flexibility, train a boosting ensemble using fitensemble. To train a multiclass model using any of the binary classifier methods GentleBoost, LogitBoost, and RobustBoost, create an ensemble template using templateEnsemble, and then pass it and the training data to fitcecoc.

Apps

Classification Learner Train models to classify data using supervised machine learning

Functions

fitensemble Fitted ensemble for classification or regression
templateEnsemble Ensemble learning template
predict Predict classification
predict Predict response of ensemble
fitcecoc Fit multiclass models for support vector machines or other classifiers
predict Predict labels for error-correcting output code multiclass classifiers
loss Classification error
crossval Cross validate ensemble
predictorImportance Estimates of predictor importance
resume Resume training ensemble
loss Regression error
crossval Cross validate ensemble
cvshrink Cross validate shrinking (pruning) ensemble
predictorImportance Estimates of predictor importance
resume Resume training ensemble
loss Classification loss for error-correcting output code multiclass classifiers
crossval Cross-validated, error-correcting output code multiclass model

Classes

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

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