Node Connectivity
There are 2933 nodes that can be used as successor
for a node with an output port of type 
Table.
KStar (3.6) (legacy)
K* is an instance-based classifier, that is the class of a test instance is based upon the class of those training instances similar to it, as determined by […]
LBR (3.6) (legacy)
Lazy Bayesian Rules Classifier. The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute […]
LWL (3.6) (legacy)
Locally weighted learning. Uses an instance-based algorithm to assign instance weights which are then used by a specified WeightedInstancesHandler. Can do […]
ClassBalancedND (3.6) (legacy)
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure. For more info, check Lin […]
DataNearBalancedND (3.6) (legacy)
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random data-balanced tree structure. For more info, check Lin […]
ND (3.6) (legacy)
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random tree structure. For more info, check Lin Dong, Eibe […]
AdaBoostM1 (3.6) (legacy)
Class for boosting a nominal class classifier using the Adaboost M1 method. Only nominal class problems can be tackled. Often dramatically improves […]
AdditiveRegression (3.6) (legacy)
Meta classifier that enhances the performance of a regression base classifier. Each iteration fits a model to the residuals left by the classifier on the […]
AttributeSelectedClassifier (3.6) (legacy)
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
Bagging (3.6) (legacy)
Class for bagging a classifier to reduce variance. Can do classification and regression depending on the base learner. For more information, see Leo […]