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## Uses of Class
edu.uci.ics.jung.algorithms.IterativeProcess

Packages that use IterativeProcess
edu.uci.ics.jung.algorithms.flows | Provides a series of methods for solving the s-t max flow and other network flow problems.
edu.uci.ics.jung.algorithms.importance | Provides a set of algorithms for computing the importance of each node (or edge) in a graph relative to all others (or, for the algorithms that inherit from `RelativeAuthorityRanker`, relative to a specified subset of elements).

Uses of IterativeProcess in edu.uci.ics.jung.algorithms.flows

Subclasses of IterativeProcess in edu.uci.ics.jung.algorithms.flows
`class` | `EdmondsKarpMaxFlow` Implements the EdmondsKarpMaxFlow algorithm for solving the maximum flow problem.

Uses of IterativeProcess in edu.uci.ics.jung.algorithms.importance

Subclasses of IterativeProcess in edu.uci.ics.jung.algorithms.importance
`class` | `AbstractRanker` Abstract class for algorithms that rank nodes or edges by some "importance" metric.
`class` | `BaryCenter` A simple node importance ranker based on the total shortest path of the node.
`class` | `BetweennessCentrality` Computes betweenness centrality for each vertex and edge in the graph.
`class` | `DegreeDistributionRanker` A simple node importance ranker based on the degree of the node.
`class` | `HITS` Calculates the "hubs-and-authorities" importance measures for each node in a graph.
`class` | `HITSWithPriors` Algorithm that extends the HITS algorithm by incorporating root nodes (priors).
`class` | `KStepMarkov` Algorithm variant of `PageRankWithPriors` that computes the importance of a node based upon taking fixed-length random walks out from the root set and then computing the stationary probability of being at each node.
`class` | `MarkovCentrality`
`class` | `PageRank` This algorithm measures the importance of a node in terms of the fraction of time spent at that node relative to all other nodes.
`class` | `PageRankWithPriors` Algorithm that extends the PageRank algorithm by incorporating root nodes (priors).
`class` | `RandomWalkBetweenness` Computes betweenness centrality for each vertex in the graph.
`class` | `RandomWalkSTBetweenness` /** Computes s-t betweenness centrality for each vertex in the graph.
`class` | `RelativeAuthorityRanker` This class provides basic infrastructure for relative authority algorithms that compute the importance of nodes relative to one or more root nodes.
`class` | `WeightedNIPaths` This algorithm measures the importance of nodes based upon both the number and length of disjoint paths that lead to a given node from each of the nodes in the root set.

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