Node Connectivity
There are 99 nodes that can be used as predessesor
for a node with an input port of type 
Weka 3.6 Classifier.
RandomCommittee (3.6) (legacy)
Class for building an ensemble of randomizable base classifiers. Each base classifiers is built using a different random number seed (but based one the same […]
RandomSubSpace (3.6) (legacy)
This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows […]
RegressionByDiscretization (3.6) (legacy)
A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized. The predicted value is the […]
RotationForest (3.6) (legacy)
Class for construction a Rotation Forest. Can do classification and regression depending on the base learner. For more information, see Juan J. […]
Stacking (3.6) (legacy)
Combines several classifiers using the stacking method. Can do classification or regression. For more information, see David H. Wolpert (1992). Stacked […]
StackingC (3.6) (legacy)
Implements StackingC (more efficient version of stacking). For more information, see A.K. Seewald: How to Make Stacking Better and Faster While Also […]
ThresholdSelector (3.6) (legacy)
A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier. The midpoint threshold is set so that a given performance […]
Vote (3.6) (legacy)
Class for combining classifiers. Different combinations of probability estimates for classification are available. For more information see: Ludmila I. […]
HyperPipes (3.6) (legacy)
Class implementing a HyperPipe classifier. For each category a HyperPipe is constructed that contains all points of that category (essentially records the […]
SerializedClassifier (3.6) (legacy)
A wrapper around a serialized classifier model. This classifier loads a serialized models and uses it to make predictions. Warning: since the serialized […]