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.
AttributeSelectedClassifier (3.7)
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier
Bagging (3.7)
Class for bagging a classifier to reduce variance
CVParameterSelection (3.7)
Class for performing parameter selection by cross-validation for any classifier. For more information, see: R
ClassificationViaClustering (3.7)
A simple meta-classifier that uses a clusterer for classification
ClassificationViaRegression (3.7)
Class for doing classification using regression methods
CostSensitiveClassifier (3.7)
A metaclassifier that makes its base classifier cost-sensitive
Dagging (3.7)
This meta classifier creates a number of disjoint, stratified folds out of the data and feeds each chunk of data to a copy of the supplied base classifier
Decorate (3.7)
DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples
END (3.7)
A meta classifier for handling multi-class datasets with 2-class classifiers by building an ensemble of nested dichotomies. For more info, check Lin Dong, […]
EnsembleSelection (3.7)
Combines several classifiers using the ensemble selection method