public class EigenvectorCentrality<V,E> extends PageRank<V,E>
disappearing_potential
alpha, vertex_priors
edge_weights, graph, hyperedges_are_self_loops, max_delta, max_iterations, output_reversed, tolerance, total_iterations
Constructor and Description |
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EigenvectorCentrality(edu.uci.ics.jung.graph.Hypergraph<V,E> graph)
Creates an instance with the specified graph and default edge weights.
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EigenvectorCentrality(edu.uci.ics.jung.graph.Hypergraph<V,E> graph,
org.apache.commons.collections4.Transformer<E,? extends java.lang.Number> edge_weights)
Creates an instance with the specified graph and edge weights.
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afterStep, collectDisappearingPotential, update
getAlpha, getVertexPrior, getVertexPriors, initialize
acceptDisconnectedGraph, done, evaluate, getAdjustedIncidentCount, getCurrentValue, getEdgeWeight, getEdgeWeights, getIterations, getMaxIterations, getOutputValue, getTolerance, getVertexScore, isDisconnectedGraphOK, setCurrentValue, setEdgeWeights, setHyperedgesAreSelfLoops, setMaxIterations, setOutputValue, setTolerance, step, swapOutputForCurrent, updateMaxDelta
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getVertexScore
public EigenvectorCentrality(edu.uci.ics.jung.graph.Hypergraph<V,E> graph, org.apache.commons.collections4.Transformer<E,? extends java.lang.Number> edge_weights)
UniformDegreeWeight
for one way to handle this for
undirected graphs.)graph
- the graph for which the centrality is to be calculatededge_weights
- the edge weights