|
||||||||||
PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
See:
Description
Interface Summary | |
---|---|
GraphClusterer | Interface for finding clusters (sets of possibly overlapping vertices) in graphs. |
Class Summary | |
---|---|
BicomponentClusterer | Finds all biconnected components (bicomponents) of an undirected graph. |
ClusterSet | A data structure representing the clusters, connected set of vertices (or edges), in a graph. |
EdgeBetweennessClusterer | An algorithm for computing clusters (community structure) in graphs based on edge betweenness. |
EdgeClusterSet | A ClusterSet where each cluster is a set of edge |
ExactFlowCommunity | ExactFlowCommunity is an algorithm that uses a set of root nodes that are supposed to be representative of a community to find the entire community using principles based on max-flow/min-cut. |
KMeansClusterer | Groups Objects into a specified number of clusters, based on their proximity in d-dimensional space, using the k-means algorithm. |
VertexClusterSet | A ClusterSet where each cluster is a set of vertices |
VoltageClusterer | Clusters vertices of a Graph based on their ranks as
calculated by VoltageRanker . |
WeakComponentClusterer | Finds all weak components in a graph where a weak component is defined as a maximal subgraph in which all pairs of vertices in the subgraph are reachable from one another in the underlying undirected subgraph. |
Exception Summary | |
---|---|
KMeansClusterer.NotEnoughClustersException | An exception that indicates that the specified data points cannot be clustered into the number of clusters requested by the user. |
Provides a series of methods for locating clusters in graphs according to some model-based, heuristic or graph-theoretic criteria.
|
||||||||||
PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |