Node Connectivity
There are 4972 nodes that can be used as predessesor
for a node with an input port of type 
Generic Port.
FilteredClusterer (3.6) (legacy)
Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter. Like the clusterer, the structure of the filter is based […]
MakeDensityBasedClusterer (3.6) (legacy)
Class for wrapping a Clusterer to make it return a distribution and density. Fits normal distributions and discrete distributions within each cluster […]
OPTICS (3.6) (legacy)
Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Joerg Sander: OPTICS: Ordering Points To Identify the Clustering Structure. In: ACM SIGMOD […]
SimpleKMeans (3.6) (legacy)
Cluster data using the k means algorithm. Can use either the Euclidean distance (default) or the Manhattan distance. If the Manhattan distance is used, then […]
XMeans (3.6) (legacy)
Cluster data using the X-means algorithm. X-Means is K-Means extended by an Improve-Structure part In this part of the algorithm the centers are attempted […]
sIB (3.6) (legacy)
Cluster data using the sequential information bottleneck algorithm. Note: only hard clustering scheme is supported. sIB assign for each instance the […]
Weka Cluster Assigner (3.6) (legacy)
The Weka Cluster Assigner takes a cluster model generated in a weka node and assigns the data at the inport to the corresponding clusters.
Weka Predictor (3.6) (legacy)
The Weka Predictor takes a model generated in a weka node and classifies the test data at the inport.
Weka Predictor (3.6) (legacy)
The Weka Predictor takes a model generated in a weka node and classifies the test data at the inport.
Weka Classifier Reader (3.6) (legacy)
Reads a weka classification model from a (zip) file.