Class AbstractIterativeScorerWithPriors<V,E,S>
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- edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer<V,E,S>
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- edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorerWithPriors<V,E,S>
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- Type Parameters:
V
- the vertex typeE
- the edge typeS
- the score type
- All Implemented Interfaces:
VertexScorer<V,S>
,IterativeContext
- Direct Known Subclasses:
HITSWithPriors
,PageRankWithPriors
public abstract class AbstractIterativeScorerWithPriors<V,E,S> extends AbstractIterativeScorer<V,E,S> implements VertexScorer<V,S>
An abstract class for iterative random-walk-based vertex scoring algorithms that have a fixed probability, for each vertex, of 'jumping' to that vertex at each step in the algorithm (rather than following a link out of that vertex).
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Field Summary
Fields Modifier and Type Field Description protected double
alpha
The probability of making a 'jump' at each step.protected org.apache.commons.collections4.Transformer<V,? extends S>
vertex_priors
The prior probability of each vertex being visited on a given 'jump' (non-link-following) step.-
Fields inherited from class edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer
edge_weights, graph, hyperedges_are_self_loops, max_delta, max_iterations, output_reversed, tolerance, total_iterations
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Constructor Summary
Constructors Constructor Description AbstractIterativeScorerWithPriors(edu.uci.ics.jung.graph.Hypergraph<V,E> g, org.apache.commons.collections4.Transformer<E,? extends java.lang.Number> edge_weights, org.apache.commons.collections4.Transformer<V,? extends S> vertex_priors, double alpha)
Creates an instance for the specified graph, edge weights, vertex priors, and jump probability.AbstractIterativeScorerWithPriors(edu.uci.ics.jung.graph.Hypergraph<V,E> g, org.apache.commons.collections4.Transformer<V,? extends S> vertex_priors, double alpha)
Creates an instance for the specified graph, vertex priors, and jump probability, with edge weights specified by the subclass.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
getAlpha()
Returns the probability of making a 'jump' (non-link-following step).protected S
getVertexPrior(V v)
Returns the prior probability forv
.org.apache.commons.collections4.Transformer<V,? extends S>
getVertexPriors()
Returns a Transformer which maps each vertex to its prior probability.void
initialize()
Initializes the state of this instance.-
Methods inherited from class edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer
acceptDisconnectedGraph, afterStep, collectDisappearingPotential, done, evaluate, getAdjustedIncidentCount, getCurrentValue, getEdgeWeight, getEdgeWeights, getIterations, getMaxIterations, getOutputValue, getTolerance, getVertexScore, isDisconnectedGraphOK, setCurrentValue, setEdgeWeights, setHyperedgesAreSelfLoops, setMaxIterations, setOutputValue, setTolerance, step, swapOutputForCurrent, update, updateMaxDelta
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface edu.uci.ics.jung.algorithms.scoring.VertexScorer
getVertexScore
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Constructor Detail
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AbstractIterativeScorerWithPriors
public AbstractIterativeScorerWithPriors(edu.uci.ics.jung.graph.Hypergraph<V,E> g, org.apache.commons.collections4.Transformer<E,? extends java.lang.Number> edge_weights, org.apache.commons.collections4.Transformer<V,? extends S> vertex_priors, double alpha)
Creates an instance for the specified graph, edge weights, vertex priors, and jump probability.- Parameters:
g
- the graph whose vertices are to be assigned scoresedge_weights
- the edge weights to use in the score assignmentvertex_priors
- the prior probabilities of each vertex being 'jumped' toalpha
- the probability of making a 'jump' at each step
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AbstractIterativeScorerWithPriors
public AbstractIterativeScorerWithPriors(edu.uci.ics.jung.graph.Hypergraph<V,E> g, org.apache.commons.collections4.Transformer<V,? extends S> vertex_priors, double alpha)
Creates an instance for the specified graph, vertex priors, and jump probability, with edge weights specified by the subclass.- Parameters:
g
- the graph whose vertices are to be assigned scoresvertex_priors
- the prior probabilities of each vertex being 'jumped' toalpha
- the probability of making a 'jump' at each step
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Method Detail
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initialize
public void initialize()
Initializes the state of this instance.- Overrides:
initialize
in classAbstractIterativeScorer<V,E,S>
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getVertexPrior
protected S getVertexPrior(V v)
Returns the prior probability forv
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v
- the vertex whose prior probability is being queried- Returns:
- the prior probability for
v
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getVertexPriors
public org.apache.commons.collections4.Transformer<V,? extends S> getVertexPriors()
Returns a Transformer which maps each vertex to its prior probability.- Returns:
- a Transformer which maps each vertex to its prior probability
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getAlpha
public double getAlpha()
Returns the probability of making a 'jump' (non-link-following step).- Returns:
- the probability of making a 'jump' (non-link-following step)
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