Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV LETTER NEXT LETTER | FRAMES NO FRAMES

A B C D E F G H I J K L M N O P R S T U V W X Y Z

## K

KEY - Static variable in class edu.uci.ics.jung.algorithms.importance.BaryCenter
KEY - Static variable in class edu.uci.ics.jung.algorithms.importance.DegreeDistributionRanker
KEY - Static variable in class edu.uci.ics.jung.algorithms.importance.PageRank
KKLayout - class edu.uci.ics.jung.visualization.contrib.KKLayout.
  Implements the Kamada-Kawai algorithm for node layout.
KKLayout(Graph) - Constructor for class edu.uci.ics.jung.visualization.contrib.KKLayout
KKLayout(Graph, Distance) - Constructor for class edu.uci.ics.jung.visualization.contrib.KKLayout
KKLayout - class samples.preview_new_graphdraw.iterablelayouts.KKLayout.
  Implements the Kamada-Kawai algorithm for node layout.
KKLayout() - Constructor for class samples.preview_new_graphdraw.iterablelayouts.KKLayout
KKLayout(double) - Constructor for class samples.preview_new_graphdraw.iterablelayouts.KKLayout
KKLayoutInt - class edu.uci.ics.jung.visualization.contrib.KKLayoutInt.
  Implements the Kamada-Kawai algorithm for node layout, tweaked to store vertex distances as integers.
KKLayoutInt(Graph) - Constructor for class edu.uci.ics.jung.visualization.contrib.KKLayoutInt
KMeansClusterer - class edu.uci.ics.jung.algorithms.cluster.KMeansClusterer.
  Groups Objects into a specified number of clusters, based on their proximity in d-dimensional space, using the k-means algorithm.
KMeansClusterer(int, double) - Constructor for class edu.uci.ics.jung.algorithms.cluster.KMeansClusterer
  Creates an instance for which calls to `cluster` will terminate when either of the two following conditions is true:
  the number of iterations is > `max_iterations`
  none of the centroids has moved as much as `convergence_threshold` since the previous iteration
KMeansClusterer.NotEnoughClustersException - exception edu.uci.ics.jung.algorithms.cluster.KMeansClusterer.NotEnoughClustersException.
  An exception that indicates that the specified data points cannot be clustered into the number of clusters requested by the user.
KMeansClusterer.NotEnoughClustersException() - Constructor for class edu.uci.ics.jung.algorithms.cluster.KMeansClusterer.NotEnoughClustersException
KNeighborhoodExtractor - class edu.uci.ics.jung.algorithms.connectivity.KNeighborhoodExtractor.
  Extracts the subgraph (neighborhood) from a graph whose nodes are no more than distance k away from at least one of the root nodes (starting vertices).
KNeighborhoodExtractor() - Constructor for class edu.uci.ics.jung.algorithms.connectivity.KNeighborhoodExtractor
KNeighborhoodFilter - class edu.uci.ics.jung.graph.filters.impl.KNeighborhoodFilter.
  A filter used to extract the k-neighborhood around one or more root node(s)
KNeighborhoodFilter(Set, int, int) - Constructor for class edu.uci.ics.jung.graph.filters.impl.KNeighborhoodFilter
  Constructs a new instance of the filter
KNeighborhoodFilter(Vertex, int, int) - Constructor for class edu.uci.ics.jung.graph.filters.impl.KNeighborhoodFilter
  Constructs a new instance of the filter
KPartiteEdgePredicate - class edu.uci.ics.jung.graph.predicates.KPartiteEdgePredicate.
  An edge predicate that passes `Edge`s whose endpoints satisfy distinct elements of the Predicate collection passed in as a parameter to the constructor.
KPartiteEdgePredicate(Collection) - Constructor for class edu.uci.ics.jung.graph.predicates.KPartiteEdgePredicate
KPartiteGraph - interface edu.uci.ics.jung.graph.KPartiteGraph.
  An interface for k-partite graphs.
KPartiteSparseGraph - class edu.uci.ics.jung.graph.impl.KPartiteSparseGraph.
  An implementation of KPartiteGraph based on SparseGraph.
KPartiteSparseGraph(Collection, boolean) - Constructor for class edu.uci.ics.jung.graph.impl.KPartiteSparseGraph
  Creates a KPartiteSparseGraph whose partitions are specified by the predicates in the `partitions` array.
KPartiteSparseGraph(Graph, Collection, boolean) - Constructor for class edu.uci.ics.jung.graph.impl.KPartiteSparseGraph
  Creates a new `KPartiteSparseGraph` which contains all the vertices and edges in `g`.
KStepMarkov - class edu.uci.ics.jung.algorithms.importance.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.
KStepMarkov(DirectedGraph, Set, int, String) - Constructor for class edu.uci.ics.jung.algorithms.importance.KStepMarkov
  Construct the algorihm instance and initializes the algorithm.
KleinbergSmallWorldGenerator - class edu.uci.ics.jung.random.generators.KleinbergSmallWorldGenerator.
  Graph generator that produces a random graph with small world properties.
KleinbergSmallWorldGenerator(int, double) - Constructor for class edu.uci.ics.jung.random.generators.KleinbergSmallWorldGenerator
  Constructs the small world graph generator.
KullbackLeibler(double[], double[]) - Static method in class edu.uci.ics.jung.statistics.DiscreteDistribution
  Returns the Kullback-Leibler divergence between the two specified distributions, which must have the same number of elements.
key - Variable in class edu.uci.ics.jung.graph.decorators.UserDatumNumberEdgeValue
key - Variable in class edu.uci.ics.jung.graph.decorators.UserDatumNumberVertexValue
key - Variable in class edu.uci.ics.jung.graph.predicates.ContainsUserDataKeyVertexPredicate
key - Variable in class edu.uci.ics.jung.visualization.PersistentLayoutImpl
  a key for this class
key_meta_map - Static variable in class edu.uci.ics.jung.utils.UnifiedUserData
kmc - Variable in class edu.uci.ics.jung.algorithms.cluster.VoltageClusterer
kurtosis() - Method in class edu.uci.ics.jung.statistics.Histogram
  Returns the kurtosis of the values accumulated in the histogram bins.
kurtosis() - Method in class edu.uci.ics.jung.statistics.StatisticalMoments
  The kurtosis measures the sharpness of the distribution near the maximum.

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV LETTER NEXT LETTER | FRAMES NO FRAMES

A B C D E F G H I J K L M N O P R S T U V W X Y Z