There are 9 nodes that can be used as predessesor for a node with an input port of type Weka Cluster.
Martin Ester, Hans-Peter Kriegel, Joerg Sander, Xiaowei Xu: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise.
Class for wrapping a Clusterer to make it return a distribution and density.
Simple EM (expectation maximisation) class.
Cluster data using the FarthestFirst algorithm.
Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter.
Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Joerg Sander: OPTICS: Ordering Points To Identify the Clustering Structure.
Cluster data using the k means algorithm.
Cluster data using the X-means algorithm.
Reads a weka clustering model from a (zip) file.
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