Node Connectivity
There are 120 nodes that can be used as predessesor
for a node with an input port of type 
Weka 3.7 Classifier.
RandomTree (3.7)
Class for constructing a tree that considers K randomly chosen attributes at each node
SimpleCart (3.7)
Class implementing minimal cost-complexity pruning. Note when dealing with missing values, use "fractional instances" method instead of surrogate split […]
JCBA (3.7)
A Java implementation of the CBA algorithm
WeightedClassifier (3.7)
Classifier that weights a set of class association rules
ConjunctiveRule (3.7)
This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels. A rule consists of antecedents "AND"ed […]
DTNB (3.7)
Class for building and using a decision table/naive bayes hybrid classifier
DecisionTable (3.7)
Class for building and using a simple decision table majority classifier. For more information see: Ron Kohavi: The Power of Decision Tables
FURIA (3.7)
FURIA: Fuzzy Unordered Rule Induction Algorithm Details please see: Jens Christian Huehn, Eyke Huellermeier (2009)
JRip (3.7)
This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W
LAC (3.7)
Implements the LAC (Lazy Associative Classifier) algorithm, which uses associative rules to execute classifications