netkit.classifiers.active.graphfunctions
Class LabelClosenessRank

java.lang.Object
  netkit.classifiers.active.graphfunctions.ScoringFunction
      netkit.classifiers.active.graphfunctions.ReverseScoringFunction
          netkit.classifiers.active.graphfunctions.LabelClosenessRank

All Implemented Interfaces:

java.util.Comparator<PickLabelStrategy.LabelNode>

public class LabelClosenessRank
extends ReverseScoringFunction

For label closeness, we want to pick the largest closeness first, so that means we reverse normal sorting order

Field Summary

Fields inherited from class netkit.classifiers.active.graphfunctions.ScoringFunction

gm, labeler, labels

Constructor Summary

LabelClosenessRank()

Method Summary

boolean	clusterBased() Is this scoring function cluster based (does it need clustering).
double	score(ModularityClusterer.Cluster c, Node n)
java.lang.String	toString()
double	update(ModularityClusterer.Cluster c, double currentScore, Node n, Node[] newPicks) Return the new score of a node given its old score and a newly labeled node.
boolean	updateable() returns whether the score of a node will change if more nodes are labeled.

Methods inherited from class netkit.classifiers.active.graphfunctions.ReverseScoringFunction

bestScore, compare, worstScore

Methods inherited from class netkit.classifiers.active.graphfunctions.ScoringFunction

compare, initialize

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Comparator

equals

Constructor Detail

LabelClosenessRank

public LabelClosenessRank()

Method Detail

clusterBased

public boolean clusterBased()

Description copied from class: ScoringFunction

Is this scoring function cluster based (does it need clustering).

Overrides:

clusterBased in class ScoringFunction

Returns:

false (default)

toString

public java.lang.String toString()

Specified by:

toString in class ScoringFunction

score

public double score(ModularityClusterer.Cluster c,
                    Node n)

Specified by:

score in class ScoringFunction

update

public double update(ModularityClusterer.Cluster c,
                     double currentScore,
                     Node n,
                     Node[] newPicks)

Description copied from class: ScoringFunction

Return the new score of a node given its old score and a newly labeled node. By default a scoring function is not updateable and will just return the current score.

Overrides:

update in class ScoringFunction

Returns:

the current score.

updateable

public boolean updateable()

Description copied from class: ScoringFunction

returns whether the score of a node will change if more nodes are labeled. The default is that a scoring function is not updateable.

Overrides:

updateable in class ScoringFunction

Returns:

false.