There are 2933 nodes that can be used as successor
for a node with an output port of type Table.
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.
Class implementing an Apriori-type algorithm.
Class for running an arbitrary associator on data that has been passed through an arbitrary filter.
Class implementing a GSP algorithm for discovering sequential patterns in a sequential data set.