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Class Summary |
| AbstractClusterer |
Abstract superclass of clusterers which defines the I/O behavior. |
| AbstractLinkageMethod |
This class provides the basic functionality for all linkage methods of agglomerative clustering. |
| Agglomeration |
This is a simple data structure for returning an agglomeration of two clusters with a distance within
one method return. |
| AgglomerativeClustering |
This operator implements agglomerative clustering, providing the three different strategies
SingleLink, CompleteLink and AverageLink. |
| AverageLinkageMethod |
This class provides the AverageLinkageMethod, also called UPGMA, for the
agglomerative clustering operator. |
| CompleteLinkageMethod |
This class provides the complete linkage method for the AgglomerativeClustering. |
| DBScan |
This operator provides the DBScan cluster algorithm. |
| DistanceMatrix |
This class implements an symetrical matrix for distances, thus saving half the memory
by saving only the upper right triangle |
| ExampleSet2ClusterModel |
This operator creates a flat cluster model using a nominal attribute and dividing the exampleset by this attribute
over the clusters. |
| GenericWekaClustererAdaptor |
This operator performs the Weka clustering scheme with the same name. |
| KernelKMeans |
This operator is an implementation of kernel k means. |
| KMeans |
This operator represents an implementation of k-means. |
| KMedoids |
This operator represents an implementation of k-medoids. |
| RandomClustering |
Returns a random clustering. |
| SingleLinkageMethod |
This class gives the distance update function for the SingleLinkClustering of the
agglomerative clustering. |
| SVCExampleSet |
Example set that supports SVClustering. |
| SVClustering |
An implementation of Support Vector Clustering based on [BenHur/etal/2001a]. |
| SVClusteringAlgorithm |
SVClustering. |
| TopDownClustering |
A top-down generic clustering that can be used with any (flat) clustering as
inner operator. |