Node Connectivity
There are 5696 nodes that can be used as predessesor
for a node with an input port of type 
Generic Port.
SimpleLinearRegression (3.6) (legacy)
Learns a simple linear regression model. Picks the attribute that results in the lowest squared error. Missing values are not allowed. Can only deal with […]
SimpleLogistic (3.6) (legacy)
Classifier for building linear logistic regression models. LogitBoost with simple regression functions as base learners is used for fitting the logistic […]
VotedPerceptron (3.6) (legacy)
Implementation of the voted perceptron algorithm by Freund and Schapire. Globally replaces all missing values, and transforms nominal attributes into binary […]
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 […]