Node Connectivity
There are 2898 nodes that can be used as successor
for a node with an output port of type 
Table.
Grading (3.6) (legacy)
Implements Grading. The base classifiers are "graded". For more information, see A.K. Seewald, J. Fuernkranz: An Evaluation of Grading Classifiers. In: […]
GridSearch (3.6) (legacy)
Performs a grid search of parameter pairs for the a classifier (Y-axis, default is LinearRegression with the "Ridge" parameter) and the PLSFilter (X-axis, […]
LogitBoost (3.6) (legacy)
Class for performing additive logistic regression. This class performs classification using a regression scheme as the base learner, and can handle […]
MetaCost (3.6) (legacy)
This metaclassifier makes its base classifier cost-sensitive using the method specified in Pedro Domingos: MetaCost: A general method for making […]
MultiBoostAB (3.6) (legacy)
Class for boosting a classifier using the MultiBoosting method. MultiBoosting is an extension to the highly successful AdaBoost technique for forming […]
MultiClassClassifier (3.6) (legacy)
A metaclassifier for handling multi-class datasets with 2-class classifiers. This classifier is also capable of applying error correcting output codes for […]
MultiScheme (3.6) (legacy)
Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data. Performance is […]
OrdinalClassClassifier (3.6) (legacy)
Meta classifier that allows standard classification algorithms to be applied to ordinal class problems. For more information see: Eibe Frank, Mark Hall: […]
RacedIncrementalLogitBoost (3.6) (legacy)
Classifier for incremental learning of large datasets by way of racing logit-boosted committees. For more information see: Eibe Frank, Geoffrey Holmes, […]
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 […]