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.
Winnow (3.6) (legacy)
Implements Winnow and Balanced Winnow algorithms by Littlestone. For more information, see N. Littlestone (1988). Learning quickly when irrelevant […]
IB1 (3.6) (legacy)
Nearest-neighbour classifier. Uses normalized Euclidean distance to find the training instance closest to the given test instance, and predicts the same […]
IBk (3.6) (legacy)
K-nearest neighbours classifier. Can select appropriate value of K based on cross-validation. Can also do distance weighting. For more information, see D. […]
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 […]