meta
This category contains 34 nodes.
OneClassClassifier (3.7)
Performs one-class classification on a dataset. Classifier reduces the class being classified to just a single class, and learns the datawithout using any […]
OrdinalClassClassifier (3.7)
Meta classifier that allows standard classification algorithms to be applied to ordinal class problems. For more information see: Eibe Frank, Mark Hall: A […]
RacedIncrementalLogitBoost (3.7)
Classifier for incremental learning of large datasets by way of racing logit-boosted committees. For more information see: Eibe Frank, Geoffrey Holmes, […]
RandomCommittee (3.7)
Class for building an ensemble of randomizable base classifiers
RandomSubSpace (3.7)
This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows […]
RealAdaBoost (3.7)
Class for boosting a 2-class classifier using the Real Adaboost method. For more information, see J
RegressionByDiscretization (3.7)
A regression scheme that employs any classifier on a copy of the data that has the class attribute discretized
RotationForest (3.7)
Class for construction a Rotation Forest
Stacking (3.7)
Combines several classifiers using the stacking method
StackingC (3.7)
Implements StackingC (more efficient version of stacking). For more information, see A.K