Node Connectivity
There are 2934 nodes that can be used as successor
for a node with an output port of type 
Table.
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 […]
Apriori (3.6) (legacy)
Class implementing an Apriori-type algorithm. Iteratively reduces the minimum support until it finds the required number of rules with the given minimum […]
FPGrowth (3.6) (legacy)
Class implementing the FP-growth algorithm for finding large item sets without candidate generation. Iteratively reduces the minimum support until it finds […]
FilteredAssociator (3.6) (legacy)
Class for running an arbitrary associator on data that has been passed through an arbitrary filter. Like the associator, the structure of the filter is […]
GeneralizedSequentialPatterns (3.6) (legacy)
Class implementing a GSP algorithm for discovering sequential patterns in a sequential data set. The attribute identifying the distinct data sequences […]