This category contains 30 nodes.
Classifier for incremental learning of large datasets by way of racing logit-boosted committees.
Class for building an ensemble of randomizable base classifiers.
This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as […]
A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized.
Combines several classifiers using the stacking method.
Implements StackingC (more efficient version of stacking).
A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier.
Class for combining classifiers. Different combinations of probability estimates for classification are available.