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.
FilteredClassifier (3.6) (legacy)
Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. Like the classifier, the structure of the filter is […]
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, […]