Node Connectivity
There are 3042 nodes that can be used as successor
for a node with an output port of type 
Table.
SMOreg (3.6) (legacy)
SMOreg implements the support vector machine for regression. The parameters can be learned using various algorithms. The algorithm is selected by setting […]
SPegasos (3.6) (legacy)
Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al. (2007). This implementation […]
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 […]