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

A

AbstractAttributeMetaInfo - Class in netkit.graph

This abstract class is used to persist certain information across an entire Graph related to a particular Attribute.

accept(Node) - Method in interface netkit.graph.NodeFilter

Tests whether or not the specified Node should be included.

active - Variable in class netkit.util.ApproximateCentralities.ApproximateCentrality

active() - Method in class netkit.util.ComputeProcess

add(Attribute) - Method in class netkit.graph.Attributes

Adds an Attribute to this container; the name of the Attribute must be a unique field name within this container.

add(String) - Method in class netkit.graph.ExpandableTokenSet

add(String) - Method in class netkit.graph.TokenSet

Adds the supplied token to this set; duplicates are not allowed.

add(ConfusionMatrix) - Method in class netkit.util.ConfusionMatrix

add(Matrix) - Method in class netkit.util.Matrix

add(E) - Method in class netkit.util.UpdatablePriorityQueue

Inserts the specified element into this priority queue.

add(double[], double[]) - Static method in class netkit.util.VectorMath

Add array 2 into array 1

addAttribute(String, Attribute) - Method in class netkit.graph.Graph

Adds an Attribute to the Attributes container represented by the supplied nodeType name.

addAttributes(Attributes) - Method in class netkit.graph.Graph

Adds the supplied Attributes container (or node type) to this Graph; Attributes must be added to the Graph before Nodes that utilize them can be added.

addCliqueToAssortMatrix(double[][], double[]) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

Utility method whch can be used by any sub-class.

addEdge(Edge) - Method in class netkit.graph.Graph

Deprecated. Use of this method is deprecated, use Graph.addEdge(EdgeType,Node,Node,double) instead

addEdge(EdgeType, Node, Node, double) - Method in class netkit.graph.Graph

Add an edge created from the supplied parameters to the graph; if the nodes are already connected, then simply add the weight to the existing Edge.

addEdge(Edge) - Method in class netkit.graph.Node

Adds the supplied edge to this node; the Edge must not already exist.

addEdges(Edge[]) - Method in class netkit.util.GraphView

Assumes EdgeType is same for all edges.

addEdgeType(EdgeType) - Method in class netkit.graph.Graph

Add the supplied EdgeType to this Graph; EdgeTypes must be added to the Graph before Edges that utilize them can be added.

addListener(ClassifierListener) - Method in interface netkit.classifiers.Classifier

addListener(ClassifierListener) - Method in class netkit.classifiers.ClassifierImp

addListener(InferenceMethodListener) - Method in class netkit.inference.InferenceMethod

addNode(String, Attributes) - Method in class netkit.graph.Graph

Adds a new Node to the Graph using the supplied node name and Attributes container.

addToken(String) - Method in class netkit.graph.AttributeExpandableCategorical

Adds the supplied token parameter to the set of valid tokens for this attribute.

addTrainingLabel(Node, int) - Method in interface netkit.classifiers.Incremental

After the model has been induced, use this method to add a new training label.

addValues() - Method in class netkit.graph.Node

If the Attributes container (AKA nodeType) has been increased in size by adding one or more Attribute fields to it, this method will resize the internal values array to match.

addWeight(double) - Method in class netkit.graph.Edge

Increments the weight field of this Edge.

aggFactory - Static variable in class netkit.classifiers.relational.NetworkClassifierImp

Get the aggregator factory, which will be used to get the aggregators needed for the classifier.

aggregateCache - Variable in class netkit.classifiers.aggregators.AggregatorImp

aggregation - Variable in class netkit.classifiers.relational.NetworkClassifierImp

What kind of aggregation should the classifier do.

Aggregator - Interface in netkit.classifiers.aggregators

The Aggregator interface provides for dynamic attribute fields within Attributes containers.

AggregatorByValue - Interface in netkit.classifiers.aggregators

The AggregatorByValue extends a normal aggregator by aggregating on a specific given attribute value (e.g., how often did 'aquavit' appear in the aggregation neighborhood).

AggregatorByValueImp - Class in netkit.classifiers.aggregators

This should be the parent class for any AggregatorByValue class.

AggregatorByValueImp(String, EdgeType, Attribute, Type, double) - Constructor for class netkit.classifiers.aggregators.AggregatorByValueImp

Specifies the core parameters needed to instantiate an AggregatorByValue class.

AggregatorFactory - Class in netkit.classifiers.aggregators

This Factory class is a singleton class which creates Aggregators.

AggregatorImp - Class in netkit.classifiers.aggregators

This should be the parent for any Aggregator class.

AggregatorImp(String, EdgeType, Attribute, Type, double) - Constructor for class netkit.classifiers.aggregators.AggregatorImp

Helper constructor for AggregatorByValueImp - an aggregator for a specific attribute value.

AggregatorImp(String, EdgeType, Attribute, Type) - Constructor for class netkit.classifiers.aggregators.AggregatorImp

Creates an aggregator that is not by value (it calls the more specific constructor with a 'value' of Double.NaN).

aggregators - Variable in class netkit.classifiers.relational.NetworkClassifierImp

This list contains all the aggregators for an input graph.

aggTypes - Variable in class netkit.classifiers.relational.NetworkClassifierImp

This array contains the list of aggregators that this classifier will use.

AL_PREFIX - Static variable in class netkit.classifiers.NetworkLearning

alpha - Variable in class netkit.util.ApproximateCentralities.ApproximateCentrality

alphaCentrality - Variable in class netkit.util.ApproximateCentralities

alstrategies - Static variable in class netkit.classifiers.NetworkLearning

applyCMN(DataSplit) - Method in class netkit.classifiers.Estimate

Apply class mass normalization.

applyLabels(int) - Method in class netkit.classifiers.DataSplit

ApproximateCentralities - Class in netkit.util

ApproximateCentralities(GraphMetrics) - Constructor for class netkit.util.ApproximateCentralities

ApproximateCentralities.ApproximateCentrality - Class in netkit.util

ApproximateCentralities.ApproximateCentrality(String, boolean) - Constructor for class netkit.util.ApproximateCentralities.ApproximateCentrality

ArrayIterator<T> - Class in netkit.util

ArrayIterator(T[]) - Constructor for class netkit.util.ArrayIterator

ArrayIterator(T[], boolean) - Constructor for class netkit.util.ArrayIterator

ArrayUtil - Class in netkit.util

ArrayUtil() - Constructor for class netkit.util.ArrayUtil

asBinaryClassification(String) - Method in class netkit.classifiers.Classification

asClassification() - Method in class netkit.classifiers.Estimate

asEdge() - Method in class netkit.graph.edgecreator.EdgeCreatorImp.NbrEntry

asEdge(Node) - Method in class netkit.graph.edgecreator.EdgeCreatorImp.NbrEntry

asString(double[][]) - Static method in class netkit.util.ArrayUtil

asString(double[]) - Static method in class netkit.util.ArrayUtil

asString(double[], int, int) - Static method in class netkit.util.ArrayUtil

asString(int[]) - Static method in class netkit.util.ArrayUtil

asString(int[], int, int) - Static method in class netkit.util.ArrayUtil

asString(T[]) - Static method in class netkit.util.ArrayUtil

asString(T[], int, int) - Static method in class netkit.util.ArrayUtil

attrib - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

attribIdx - Variable in class netkit.classifiers.aggregators.AggregatorImp

attribute - Variable in class netkit.classifiers.aggregators.AggregatorImp

attribute - Variable in class netkit.classifiers.ClassifierImp

Attribute - Class in netkit.graph

This is the abstract parent of all Attribute classes.

Attribute(String, Type) - Constructor for class netkit.graph.Attribute

Subclasses should provide a public constructor that overrides this one.

AttributeCategorical - Class in netkit.graph

This class handles attributes that are of type CATEGORICAL.

AttributeCategorical(String, TokenSet) - Constructor for class netkit.graph.AttributeCategorical

The constructor must be provided the name of this attribute and the set of valid categorical token values.

AttributeCategoricalMetaInfo - Class in netkit.graph

This class is used to persist certain information across an entire graph related to a particular AttributeCategorical.

AttributeCategoricalMetaInfo(AttributeCategorical, Attributes, Graph) - Constructor for class netkit.graph.AttributeCategoricalMetaInfo

Construct an object of this type.

AttributeContinuous - Class in netkit.graph

This class handles attributes that are of type CONTINUOUS.

AttributeContinuous(String) - Constructor for class netkit.graph.AttributeContinuous

The constructor must be provided the name for this attribute.

attributeCount() - Method in class netkit.graph.Attributes

Get the number of Attribute fields in this container including the key Attribute (if one exists).

AttributeDiscrete - Class in netkit.graph

This class handles attributes that are of type DISCRETE.

AttributeDiscrete(String) - Constructor for class netkit.graph.AttributeDiscrete

The constructor must be provided the name for this attribute.

AttributeExpandableCategorical - Class in netkit.graph

This class handles attributes that are of type CATEGORICAL.

AttributeExpandableCategorical(String, ExpandableTokenSet) - Constructor for class netkit.graph.AttributeExpandableCategorical

The constructor must be provided the name of this attribute and an ExpandableTokenSet to keep track of tokens.

AttributeExpandableCategorical(String) - Constructor for class netkit.graph.AttributeExpandableCategorical

The constructor must be provided the name of this attribute.

AttributeFixedCategorical - Class in netkit.graph

This class handles attributes that are of type CATEGORICAL.

AttributeFixedCategorical(String, FixedTokenSet) - Constructor for class netkit.graph.AttributeFixedCategorical

The constructor must be provided the name of this attribute and the set of valid categorical token values.

AttributeIgnore - Class in netkit.graph

This class handles attributes that are of type IGNORE.

AttributeIgnore(String) - Constructor for class netkit.graph.AttributeIgnore

The constructor must be provided the name for this attribute.

attributeIndex - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

AttributeKey - Class in netkit.graph

This class handles attributes that are of type KEY.

AttributeKey(String) - Constructor for class netkit.graph.AttributeKey

The constructor must be provided the name for this attribute.

AttributeMetaInfo - Class in netkit.graph

This class is used to persist certain information across an entire graph related to a particular Attribute.

AttributeMetaInfo(Attribute, Attributes, Graph) - Constructor for class netkit.graph.AttributeMetaInfo

Construct an object of this type.

Attributes - Class in netkit.graph

This class is a container for Attribute classes.

Attributes(String) - Constructor for class netkit.graph.Attributes

This constructor builds an Attributes container object using the supplied name.

attributeValue - Variable in class netkit.classifiers.aggregators.AggregatorByValueImp

attributeValue - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

augmentGraph(DataSplit, GraphView, EdgeCreator[]) - Method in class netkit.classifiers.NetworkLearning

B

BaseCategoricalEdgeCreator - Class in netkit.graph.edgecreator

BaseCategoricalEdgeCreator() - Constructor for class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

BaseNumericEdgeCreator - Class in netkit.graph.edgecreator

BaseNumericEdgeCreator() - Constructor for class netkit.graph.edgecreator.BaseNumericEdgeCreator

BayesCategoricalEdgeCreator - Class in netkit.graph.edgecreator

BayesCategoricalEdgeCreator() - Constructor for class netkit.graph.edgecreator.BayesCategoricalEdgeCreator

bestScore() - Method in class netkit.classifiers.active.graphfunctions.ReverseScoringFunction

What is the best score (first to be picked)

bestScore() - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

What is the best score (first to be picked)

Betweenness - Class in netkit.classifiers.active.graphfunctions

Betweenness() - Constructor for class netkit.classifiers.active.graphfunctions.Betweenness

buildClassifier(Instances) - Method in class netkit.classifiers.bayes.NaiveBayesMultinomial

Generates the classifier.

buildEdges() - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

buildEdges() - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

buildEdges() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

build the edges using the current edge creation model.

buildGraph() - Static method in class netkit.classifiers.DataSampler

buildModel(DataSplit) - Method in class netkit.graph.edgecreator.BayesCategoricalEdgeCreator

buildModel(DataSplit) - Method in class netkit.graph.edgecreator.CosineDistanceEdgeCreator

buildModel(DataSplit) - Method in interface netkit.graph.edgecreator.EdgeCreator

Build a model of edge creation based on the data split.

buildModel(DataSplit) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

buildModel(DataSplit) - Method in class netkit.graph.edgecreator.EuclideanDistanceEdgeCreator

buildModel(DataSplit) - Method in class netkit.graph.edgecreator.GaussianNumericEdgeCreator

buildModel(DataSplit) - Method in class netkit.graph.edgecreator.MahalanobisDistanceEdgeCreator

buildNodeArray() - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

buildNodeCluster(Set<Node>, ModularityClusterer.Cluster) - Static method in class netkit.util.ModularityClusterer

C

calcCentralityActive() - Method in class netkit.util.GraphMetrics

calcCentralityProgress() - Method in class netkit.util.GraphMetrics

calcClusterActive() - Method in class netkit.util.GraphMetrics

calcClusterProgress() - Method in class netkit.util.GraphMetrics

calcComponentActive() - Method in class netkit.util.GraphMetrics

calcComponentProgress() - Method in class netkit.util.GraphMetrics

calculateCentralityStat() - Method in class netkit.util.GraphMetrics

This calculates the all-pairs closest distances

calculateClusterStat() - Method in class netkit.util.GraphMetrics

calculateComponentStat() - Method in class netkit.util.GraphMetrics

calculateDegreeStat() - Method in class netkit.util.GraphMetrics

calculateEdgeBasedAssortativityCoeff(Classification) - Static method in class netkit.util.GraphMetrics

calculateEdgeBasedAssortativityCoeff(Classification, EdgeType) - Static method in class netkit.util.GraphMetrics

calculateEdgeBasedAssortativityCoeff(String, AttributeCategorical) - Method in class netkit.util.GraphMetrics

calculateEdgeBasedAssortativityCoeff(String, AttributeCategorical, EdgeType) - Method in class netkit.util.GraphMetrics

calculateEdgeStat() - Method in class netkit.util.GraphMetrics

calculateNodeBasedAssortativityCoeff(Classification) - Static method in class netkit.util.GraphMetrics

calculateNodeBasedAssortativityCoeff(Classification, EdgeType) - Static method in class netkit.util.GraphMetrics

calculateNodeBasedAssortativityCoeff(String, AttributeCategorical) - Method in class netkit.util.GraphMetrics

calculateNodeBasedAssortativityCoeff(String, AttributeCategorical, EdgeType) - Method in class netkit.util.GraphMetrics

canAggregate(String, Attribute) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Checks if the fully specified classname is an aggregator that can aggregate a given attribute.

canHandle(Attribute) - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

canHandle(Attribute) - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

canHandle(Attribute) - Method in class netkit.graph.edgecreator.BayesCategoricalEdgeCreator

canHandle(Attribute) - Method in class netkit.graph.edgecreator.CosineDistanceEdgeCreator

canHandle(Attribute) - Method in interface netkit.graph.edgecreator.EdgeCreator

Queries the edge creator if it can handle (i.e., create edges for) the given attribute.

canHandle(Attribute) - Method in class netkit.graph.edgecreator.EuclideanDistanceEdgeCreator

canHandle(Attribute) - Method in class netkit.graph.edgecreator.MahalanobisDistanceEdgeCreator

canHandleAttributeValue(Attribute) - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

canHandleAttributeValue(Attribute) - Method in interface netkit.graph.edgecreator.EdgeCreator

Queries the edge creator if it can handle (i.e., create edges for) the given attribute using a specific attribute value.

canHandleAttributeValue(Attribute) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

centrality - Variable in class netkit.util.ApproximateCentralities.ApproximateCentrality

chains - Variable in class netkit.inference.GibbsSampling

ClassDistribRelNeighbor - Class in netkit.classifiers.relational

The Class Distributional Relational Neighbor (ClassDistributRelNeighbor) classifier works by creating a 'prototypical' class vector for each class of node and then estimating a label for a new node by calculating how near that new node is to each of these 'class reference vectors'.

ClassDistribRelNeighbor() - Constructor for class netkit.classifiers.relational.ClassDistribRelNeighbor

Classification - Class in netkit.classifiers

Classification(Estimate) - Constructor for class netkit.classifiers.Classification

Classification(Graph, String, AttributeCategorical) - Constructor for class netkit.classifiers.Classification

Classifier - Interface in netkit.classifiers

$Id: Classifier.java,v 1.4 2004/12/12 17:43:40 sofmac Exp $ Part of the open-source Network Learning Toolkit

User: smacskassy Date: Dec 2, 2004 Time: 9:16:44 PM

ClassifierImp - Class in netkit.classifiers

$Id: ClassifierImp.java,v 1.6 2007/03/26 23:45:06 sofmac Exp $ Part of the open-source Network Learning Toolkit

User: smacskassy Date: Dec 2, 2004 Time: 9:16:44 PM

ClassifierImp() - Constructor for class netkit.classifiers.ClassifierImp

ClassifierListener - Interface in netkit.classifiers

$Id: ClassifierListener.java,v 1.2 2004/12/05 02:57:18 sofmac Exp $ Part of the open-source Network Learning Toolkit

User: smacskassy Date: Dec 1, 2004 Time: 12:07:27 AM

classify(Node) - Method in interface netkit.classifiers.Classifier

classify(Node, Classification) - Method in interface netkit.classifiers.Classifier

classify(Node) - Method in class netkit.classifiers.ClassifierImp

classify(Node, Classification) - Method in class netkit.classifiers.ClassifierImp

classify(Node, int) - Method in interface netkit.classifiers.ClassifierListener

classify(Node, int) - Method in class netkit.classifiers.Estimate

classify(Node, Estimate, boolean) - Method in interface netkit.classifiers.relational.NetworkClassifier

Classify a given node into one of the given classes.

classify(Node, Estimate, boolean) - Method in class netkit.classifiers.relational.NetworkClassifierImp

Classify a given node into one of the given classes.

classify(NetworkClassifier, Iterator<Node>) - Method in class netkit.inference.InferenceMethod

classify(NetworkClassifier, Iterator<Node>, Classification) - Method in class netkit.inference.InferenceMethod

classify(Classification, int[]) - Method in interface netkit.inference.InferenceMethodListener

classPrior - Variable in class netkit.classifiers.ClassifierImp

ClassPrior - Class in netkit.classifiers.nonrelational

This classifier is static and always returns the class marginals.

ClassPrior() - Constructor for class netkit.classifiers.nonrelational.ClassPrior

cleanup() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

clear() - Method in class netkit.classifiers.Classification

clear() - Method in class netkit.classifiers.Estimate

clear() - Method in class netkit.util.UpdatablePriorityQueue

Removes all of the elements from this priority queue.

clearListeners() - Method in interface netkit.classifiers.Classifier

clearListeners() - Method in class netkit.classifiers.ClassifierImp

clearListeners() - Method in class netkit.inference.InferenceMethod

clone() - Method in class netkit.classifiers.Classification

clone() - Method in class netkit.classifiers.DataSampler

clone() - Method in class netkit.classifiers.DataView

clone() - Method in class netkit.graph.Graph

clone() - Method in class netkit.util.Matrix

Closeness - Class in netkit.classifiers.active.graphfunctions

Closeness() - Constructor for class netkit.classifiers.active.graphfunctions.Closeness

clsIdx - Variable in class netkit.classifiers.ClassifierImp

clsIdx - Variable in class netkit.classifiers.DataSampler

clsIdx - Variable in class netkit.classifiers.DataView

clusterBased() - Method in class netkit.classifiers.active.graphfunctions.ClusterCloseness

clusterBased() - Method in class netkit.classifiers.active.graphfunctions.ClusterSizeRank

clusterBased() - Method in class netkit.classifiers.active.graphfunctions.ClusterWeightedCloseness

clusterBased() - Method in class netkit.classifiers.active.graphfunctions.LabelClosenessRank

clusterBased() - Method in class netkit.classifiers.active.graphfunctions.LabelWeightedClosenessRank

clusterBased() - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

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

ClusterCloseness - Class in netkit.classifiers.active.graphfunctions

ClusterCloseness() - Constructor for class netkit.classifiers.active.graphfunctions.ClusterCloseness

ClusterSizeRank - Class in netkit.classifiers.active.graphfunctions

ClusterSizeRank() - Constructor for class netkit.classifiers.active.graphfunctions.ClusterSizeRank

ClusterWeightedCloseness - Class in netkit.classifiers.active.graphfunctions

ClusterWeightedCloseness() - Constructor for class netkit.classifiers.active.graphfunctions.ClusterWeightedCloseness

cMap - Variable in class netkit.util.Histogram

coltMatrix - Variable in class netkit.util.GraphMetrics.AdjacencyMatrix

comparator() - Method in class netkit.util.UpdatablePriorityQueue

Returns the comparator used to order the elements in this queue, or null if this queue is sorted according to the natural ordering of its elements.

ComparatorLabeler - Class in netkit.classifiers.active

This class does a comparison between multiple active learning strategies.

ComparatorLabeler() - Constructor for class netkit.classifiers.active.ComparatorLabeler

compare(double, double) - Method in class netkit.classifiers.active.graphfunctions.ReverseScoringFunction

Reverse of default comparator function.

compare(PickLabelStrategy.LabelNode, PickLabelStrategy.LabelNode) - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

Standard comparator function.

compare(double, double) - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

Standard comparator function.

compareTo(PickLabelStrategy.LabelNode) - Method in class netkit.classifiers.active.PickLabelStrategy.LabelNode

compareTo(Edge) - Method in class netkit.graph.Edge

Specifies a natural ordering for Edges; compare EdgeTypes first, then the source Node and finally the destination Node.

compareTo(EdgeCreatorImp.NbrEntry) - Method in class netkit.graph.edgecreator.EdgeCreatorImp.NbrEntry

compareTo(Node) - Method in class netkit.graph.Node

Specifies a natural ordering for Nodes; compare node types first, then node names.

computeAssortativityFromMatrix(double[][]) - Static method in class netkit.util.GraphMetrics

Utility method which can be used by any sub-class

computeEmpiricalRisk(Estimate) - Static method in class netkit.classifiers.active.EmpiricalRiskMinimization

Compute the empirical risk for a specific set of predictions using the standard empirical risk formulation: risk(predictions) = sum over x in testset: argmin_i [ 1-f(x,i) ], where f(x,i) is the probability that x belongs to class i.

ComputeProcess - Class in netkit.util

ComputeProcess(String) - Constructor for class netkit.util.ComputeProcess

Configurable - Interface in netkit.util

$Id: Configurable.java,v 1.1 2004/12/05 02:55:59 sofmac Exp $ Part of the open-source Network Learning Toolkit

User: smacskassy Date: Dec 1, 2004 Time: 8:03:35 AM

Configuration - Class in netkit.util

Configuration() - Constructor for class netkit.util.Configuration

Configuration(Configuration) - Constructor for class netkit.util.Configuration

Configuration(InputStream) - Constructor for class netkit.util.Configuration

Configuration(Configuration, InputStream) - Constructor for class netkit.util.Configuration

configure(Configuration) - Method in class netkit.classifiers.active.ComparatorLabeler

configure(Configuration) - Method in class netkit.classifiers.active.EmpiricalRiskMinimization

configure(Configuration) - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

configure(Configuration) - Method in class netkit.classifiers.active.ERMHybrid

configure(Configuration) - Method in class netkit.classifiers.active.GraphCentralityLabeling

configure(Configuration) - Method in class netkit.classifiers.active.GreedyTruth

configure(Configuration) - Method in class netkit.classifiers.active.PickLabelStrategyImp

configure(Configuration) - Method in class netkit.classifiers.active.UncertaintyLabeling

configure(Configuration) - Method in class netkit.classifiers.ClassifierImp

configure(Configuration) - Method in class netkit.classifiers.NetworkLearning

configure(Configuration) - Method in class netkit.classifiers.nonrelational.ExternalPrior

Configure this classifier using the passed-in configuration.

configure(Configuration) - Method in class netkit.classifiers.nonrelational.LocalMetaClassifier

Configures the classifier by getting the list of classifiers to use (comma-separated list in the NetworkLearning.LC_PREFIX property.

configure(Configuration) - Method in class netkit.classifiers.nonrelational.LocalWeka

Configure this classifier by getting the Weka classifier object using the classifier and options properties in addition to anything used by the superclass.

configure(Configuration) - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

Configure this classifier object.

configure(Configuration) - Method in class netkit.classifiers.relational.NetworkClassifierImp

Configure the classifier.

configure(Configuration) - Method in class netkit.classifiers.relational.NetworkMetaClassifier

Configure this classifier by getting the Weka classifier object using the classifier and options properties in addition to anything used by the superclass.

configure(Configuration) - Method in class netkit.classifiers.relational.NetworkOnlyBayes

Configures this classifier.

configure(Configuration) - Method in class netkit.classifiers.relational.NetworkWeka

Configure this classifier by getting the Weka classifier object using the classifier and options properties in addition to anything used by the superclass.

configure(Configuration) - Method in class netkit.classifiers.relational.ProbRelationalNeighbor

This does not use the configuration.

configure(Configuration) - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

Configures the classifier with respect to laplace correction: whether to have it (and what kind) and whether tu use it only on the first iteration of collective inferencing.

configure(Configuration) - Method in class netkit.inference.GibbsSampling

configure(Configuration) - Method in class netkit.inference.InferenceMethod

configure(Configuration) - Method in class netkit.inference.RelaxationLabeling

configure(Configuration) - Method in interface netkit.util.Configurable

ConfusionMatrix - Class in netkit.util

ConfusionMatrix(AttributeCategorical) - Constructor for class netkit.util.ConfusionMatrix

ConfusionMatrix(Estimate, Classification) - Constructor for class netkit.util.ConfusionMatrix

contains(String) - Method in class netkit.graph.Attributes

Check if the specified field name is already present among the attributes in this container.

contains(String) - Method in class netkit.graph.TokenSet

Determines if a token is valid for this container.

contains(E) - Method in class netkit.util.UpdatablePriorityQueue

Returns true if this queue contains the specified element.

containsKey(String) - Method in class netkit.util.Configuration

convert - Static variable in class netkit.Netkit

copy(int) - Method in class netkit.graph.Node

The constructor must be provided with a name, an Attributes container and an index.

copyInto(Estimate) - Method in class netkit.classifiers.Estimate

CosineDistanceEdgeCreator - Class in netkit.graph.edgecreator

CosineDistanceEdgeCreator() - Constructor for class netkit.graph.edgecreator.CosineDistanceEdgeCreator

Count - Class in netkit.classifiers.aggregators

The Count aggregator counts the number of times a specific value of a given attribute is observed in the neighborhood of a node in the graph.

Count(EdgeType, Attribute, double) - Constructor for class netkit.classifiers.aggregators.Count

countNeighbors(Node, Estimate) - Method in class netkit.classifiers.aggregators.SharedNodeInfo

Count, for all relevant neighbors, how many of the neighboring attributes took on each of the possible values (weighted by the edge weight).

createEdges() - Method in interface netkit.graph.edgecreator.EdgeCreator

Create all the edges on the graph provided in the initialize method (indirectly through the DataSplit object).

createEdges() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

crossValidate(int) - Method in class netkit.classifiers.DataSampler

Create full cross-validation node sets in the form result[numsplit][0][...] is the training set for split numsplit and result[numsplit][1][...] is the test set for split numsplit.

crossValidate(int) - Method in class netkit.classifiers.DataView

currPrior - Variable in class netkit.inference.InferenceMethod

D

DataSampler - Class in netkit.classifiers

DataSampler(Node[], int) - Constructor for class netkit.classifiers.DataSampler

DataSampler(Node[], int, long) - Constructor for class netkit.classifiers.DataSampler

DataSampler(Node[], int, long, boolean, boolean, boolean) - Constructor for class netkit.classifiers.DataSampler

DataSplit - Class in netkit.classifiers

DataSplit(DataView, Node[], Node[]) - Constructor for class netkit.classifiers.DataSplit

DataView - Class in netkit.classifiers

DataView(Graph, String, AttributeCategorical) - Constructor for class netkit.classifiers.DataView

DataView(Graph, String, AttributeCategorical, long) - Constructor for class netkit.classifiers.DataView

DataView(Graph, String, AttributeCategorical, long, boolean, boolean, boolean) - Constructor for class netkit.classifiers.DataView

DataView(Graph, String, AttributeCategorical, long, boolean, boolean, boolean, boolean, boolean) - Constructor for class netkit.classifiers.DataView

delta - Variable in class netkit.util.ApproximateCentralities.ApproximateCentrality

dest - Variable in class netkit.graph.edgecreator.EdgeCreatorImp.NbrEntry

distance(double[], double[]) - Method in class netkit.util.DistanceCosine

distance(double[], double[]) - Method in class netkit.util.DistanceL1

distance(double[], double[]) - Method in class netkit.util.DistanceL2

distance(double[], double[]) - Method in interface netkit.util.DistanceMeasure

DistanceCosine - Class in netkit.util

DistanceCosine() - Constructor for class netkit.util.DistanceCosine

DistanceL1 - Class in netkit.util

DistanceL1() - Constructor for class netkit.util.DistanceL1

DistanceL2 - Class in netkit.util

DistanceL2() - Constructor for class netkit.util.DistanceL2

DistanceMeasure - Interface in netkit.util

$Id: DistanceMeasure.java,v 1.1 2004/12/01 05:34:37 sofmac Exp $ Part of the open-source Network Learning Toolkit

User: smacskassy Date: Nov 30, 2004 Time: 11:46:34 PM

distributionForInstance(Instance) - Method in class netkit.classifiers.bayes.NaiveBayesMultinomial

Calculates the class membership probabilities for the given test instance.

divide(double[], double) - Static method in class netkit.util.VectorMath

Divide array by given factor

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

Estimate how near this node's neighborhood is to each of the class vectors using a user-specified distance function (cosine by default) and normalize to produce a pseudo distribution.

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.Harmonic

Returns the prediction computer in the induceModel call.

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.MetaMultiplicative

Get the estimates from each of the underlying classifiers, multiply their respective predictions together and return a normalized distribution.

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.NetworkClassifierImp

This is the final estimation method that will be called and the only estimation method that sub-classes should implement.

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.NetworkOnlyBayes

compute class estimates.

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.NetworkWeka

Predict class labels for the given node.

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.ProbRelationalNeighbor

Estimate the label of this node by using a naive Bayesian combination of the neighbor nodes.

doEstimate(Node, double[]) - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

doPruneSingletons() - Method in class netkit.classifiers.DataView

doPruneZeroKnowledge() - Method in class netkit.classifiers.DataView

doReplacement() - Method in class netkit.classifiers.DataSampler

doReplacement() - Method in class netkit.classifiers.DataView

doStratified() - Method in class netkit.classifiers.DataSampler

doStratified() - Method in class netkit.classifiers.DataView

DotGraph - Class in netkit.graph.io

DotGraph() - Constructor for class netkit.graph.io.DotGraph

dotproduct(double[], double[]) - Static method in class netkit.util.VectorMath

dotproduct(int[], int[]) - Static method in class netkit.util.VectorMath

dynamicAggregators - Variable in class netkit.classifiers.relational.NetworkClassifierImp

This list contains the 'dynamic' aggregators...

E

EC_PREFIX - Static variable in class netkit.classifiers.NetworkLearning

Edge - Class in netkit.graph

The Edge class represents an edge in the Graph object.

Edge(EdgeType, Node, Node, double) - Constructor for class netkit.graph.Edge

The constructor requires an EdgeType, a source and destination Node and a weight.

Edge(Edge) - Constructor for class netkit.graph.Edge

Copy constructor

EdgeCreator - Interface in netkit.graph.edgecreator

EdgeCreatorImp - Class in netkit.graph.edgecreator

EdgeCreatorImp() - Constructor for class netkit.graph.edgecreator.EdgeCreatorImp

EdgeCreatorImp.NbrEntry - Class in netkit.graph.edgecreator

Utility class for sub-classes where necessary

EdgeCreatorImp.NbrEntry(Node, Node, double) - Constructor for class netkit.graph.edgecreator.EdgeCreatorImp.NbrEntry

edgecreators - Static variable in class netkit.classifiers.NetworkLearning

EdgeReaderGDA - Class in netkit.graph.io

This class reads in Edge data in the GDA format.

EdgeReaderGDA() - Constructor for class netkit.graph.io.EdgeReaderGDA

EdgeReaderRN - Class in netkit.graph.io

This class reads in Edge data in RN format.

EdgeReaderRN() - Constructor for class netkit.graph.io.EdgeReaderRN

edges - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

edgetransform - Static variable in class netkit.Netkit

EdgeTransformer - Class in netkit

EdgeTransformer(String[]) - Constructor for class netkit.EdgeTransformer

edgeType - Variable in class netkit.classifiers.aggregators.AggregatorImp

edgetype - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

EdgeType - Class in netkit.graph

This class represents an edge type for the Edge class.

EdgeType(String, String, String) - Constructor for class netkit.graph.EdgeType

The constructor requires a name, source type and destination type.

EdgeWriterRN - Class in netkit.graph.io

This class outputs Edge data in RN format.

EdgeWriterRN() - Constructor for class netkit.graph.io.EdgeWriterRN

EmpiricalRiskMinimization - Class in netkit.classifiers.active

EmpiricalRiskMinimization() - Constructor for class netkit.classifiers.active.EmpiricalRiskMinimization

EmpiricalRiskMinimizationHarmonic - Class in netkit.classifiers.active

EmpiricalRiskMinimizationHarmonic() - Constructor for class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

enhanceGraphWithAttributeEdges(String, EdgeCreator[], Map<EdgeType, Double>, boolean) - Method in class netkit.util.GraphView

epsilon - Variable in class netkit.util.ApproximateCentralities.ApproximateCentrality

equals(Object) - Method in class netkit.graph.Attributes

Indicates whether some other object is "equal to" this one; note this method assumes that each instance has a unique name and uses the name for equality purposes.

equals(Object) - Method in class netkit.graph.Edge

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class netkit.graph.EdgeType

Indicates whether some other object is "equal to" this one; note this method assumes that each instance has a unique name and uses the name for equality purposes.

equals(Object) - Method in class netkit.graph.Node

Indicates whether some other object is "equal to" this one; Nodes are equal if they share the same name and type.

equals(double[], double[]) - Static method in class netkit.util.VectorMath

check if arrays are identical

equals(double[], double[], double) - Static method in class netkit.util.VectorMath

check if arrays have at most epsilon difference at each index

ERMHybrid - Class in netkit.classifiers.active

This class duses multiple active learning strategies to pick the next candidate(s).

ERMHybrid() - Constructor for class netkit.classifiers.active.ERMHybrid

ERMRank - Class in netkit.classifiers.active.graphfunctions

ERMRank() - Constructor for class netkit.classifiers.active.graphfunctions.ERMRank

estimate(Node) - Method in interface netkit.classifiers.Classifier

estimate(Node, double[]) - Method in interface netkit.classifiers.Classifier

Estimate the probabilities that a given node into belongs to any given class.

estimate(Node, Estimate) - Method in interface netkit.classifiers.Classifier

estimate(Node) - Method in class netkit.classifiers.ClassifierImp

estimate(Node, Estimate) - Method in class netkit.classifiers.ClassifierImp

estimate(Node, double[]) - Method in interface netkit.classifiers.ClassifierListener

Estimate - Class in netkit.classifiers

Estimate(Estimate) - Constructor for class netkit.classifiers.Estimate

Estimate(Graph, String, AttributeCategorical) - Constructor for class netkit.classifiers.Estimate

Estimate(Classification) - Constructor for class netkit.classifiers.Estimate

estimate(Node, double[]) - Method in class netkit.classifiers.Estimate

estimate(Node, double[]) - Method in class netkit.classifiers.nonrelational.ClassPrior

Copies the class marginals into the 'result' array.

estimate(Node, double[]) - Method in class netkit.classifiers.nonrelational.ExternalPrior

Estimate class probabilities for the given node--returns the read in estimates.

estimate(Node, double[]) - Method in class netkit.classifiers.nonrelational.LocalWeka

Predict class labels for the given node.

estimate(Node, double[]) - Method in class netkit.classifiers.nonrelational.MetaMultiplicative

Get the estimates from each of the underlying classifiers, multiply their respective predictions together and return a normalized distribution.

estimate(Node, double[]) - Method in class netkit.classifiers.nonrelational.NullPrior

estimate(Node, double[]) - Method in class netkit.classifiers.nonrelational.UniformPrior

Fills the result array with all the same values---each class is equally likely.

estimate(Node, Estimate, double[], boolean) - Method in interface netkit.classifiers.relational.NetworkClassifier

Estimate the probabilities that a given node into belongs to any given class It may use the class estimations of other nodes and may update the prior of the given node.

estimate(Node, Estimate, boolean) - Method in interface netkit.classifiers.relational.NetworkClassifier

Estimate the probabilities that a given node into belongs to any given class It may use the class estimations of other nodes and may update the prior of the given node.

estimate(Node, Estimate, Estimate, boolean) - Method in interface netkit.classifiers.relational.NetworkClassifier

Estimate the probabilities that a given node into belongs to any given class It may use the class estimations of other nodes and may update the prior of the given node.

estimate(Node, Estimate, double[], boolean) - Method in class netkit.classifiers.relational.NetworkClassifierImp

Estimate the probabilities that a given node into belongs to any given class It may use the class estimations of other nodes and may update the prior of the given node.

estimate(Node, Estimate, boolean) - Method in class netkit.classifiers.relational.NetworkClassifierImp

Estimate the probabilities that a given node into belongs to any given class It may use the class estimations of other nodes and may update the prior of the given node.

estimate(Node, Estimate, Estimate, boolean) - Method in class netkit.classifiers.relational.NetworkClassifierImp

Estimate the probabilities that a given node into belongs to any given class It may use the class estimations of other nodes and may update the prior of the given node.

estimate(Node, double[]) - Method in class netkit.classifiers.relational.NetworkClassifierImp

Estimate the probabilities that a given node into belongs to any given class.

estimate(NetworkClassifier, Iterator<Node>) - Method in class netkit.inference.InferenceMethod

estimate(NetworkClassifier, Iterator<Node>, Estimate) - Method in class netkit.inference.InferenceMethod

estimate(Estimate, int[]) - Method in interface netkit.inference.InferenceMethodListener

EuclideanDistanceEdgeCreator - Class in netkit.graph.edgecreator

EuclideanDistanceEdgeCreator() - Constructor for class netkit.graph.edgecreator.EuclideanDistanceEdgeCreator

Exist - Class in netkit.classifiers.aggregators

The Exist aggregator returns whether a specific value of a given attribute is observed in the neighborhood of a node in the graph.

Exist(EdgeType, Attribute, double) - Constructor for class netkit.classifiers.aggregators.Exist

ExpandableTokenSet - Class in netkit.graph

This class keeps track of valid tokens for a CATEGORICAL attribute type.

ExpandableTokenSet() - Constructor for class netkit.graph.ExpandableTokenSet

ExternalPrior - Class in netkit.classifiers.nonrelational

This classifier reads in estimates from a user-specified file.

ExternalPrior() - Constructor for class netkit.classifiers.nonrelational.ExternalPrior

F

Factory<T> - Class in netkit.util

Factory(String) - Constructor for class netkit.util.Factory

fields - Variable in class netkit.graph.io.SplitParser

A String array used for returning the parsed input.

FixedTokenSet - Class in netkit.graph

This class keeps track of valid tokens for a CATEGORICAL attribute type.

FixedTokenSet(String[]) - Constructor for class netkit.graph.FixedTokenSet

This constructor takes a String array of valid tokens; the tokens supplied to the constructor are the only valid ones for the lifetime of this token set.

format(LogRecord) - Method in class netkit.util.LogRecordFormatter

formatForOutput(double) - Method in class netkit.graph.Attribute

Formats the supplied value from this attribute as a String for output.

formatForOutput(double) - Method in class netkit.graph.AttributeCategorical

formatForOutput(double) - Method in class netkit.graph.AttributeContinuous

formatForOutput(double) - Method in class netkit.graph.AttributeDiscrete

formatForOutput(double) - Method in class netkit.graph.AttributeIgnore

G

GaussianNumericEdgeCreator - Class in netkit.graph.edgecreator

GaussianNumericEdgeCreator() - Constructor for class netkit.graph.edgecreator.GaussianNumericEdgeCreator

generateAggregators() - Method in class netkit.classifiers.relational.NetworkClassifierImp

This generates all the aggregator instances needed to create all the aggregated values for all the attributes as directed by the configuration.

get(String) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Get an instance of the fully named aggregator.

get(String, Configuration) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Get an instance of the fully named aggregator using a given Configuration map.

get(String, EdgeType, Attribute) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Get an instance of the named general attribute aggregator for the given relation and attribute.

get(String, EdgeType, Attribute, Configuration) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Get an instance of the named general attribute aggregator for the given relation and attribute.

get(String, EdgeType, Attribute, double) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Get an instance of the named attribute aggregator-by-value for the given relation, attribute and value.

get(String, EdgeType, Attribute, double, Configuration) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Get an instance of the named attribute aggregator-by-value for the given relation, attribute and value.

get(String, EdgeType[], Attribute) - Method in class netkit.classifiers.aggregators.AggregatorFactory

This is not yet supported.

get(String, EdgeType[], Attribute, Configuration) - Method in class netkit.classifiers.aggregators.AggregatorFactory

This is not yet supported.

get(String, EdgeType[], Attribute, double) - Method in class netkit.classifiers.aggregators.AggregatorFactory

This is not yet supported.

get(String, EdgeType[], Attribute, double, Configuration) - Method in class netkit.classifiers.aggregators.AggregatorFactory

This is not yet supported.

get(String) - Method in class netkit.util.Configuration

get(String, String) - Method in class netkit.util.Configuration

get(String) - Method in class netkit.util.Factory

get(String, Configuration) - Method in class netkit.util.Factory

get(String) - Static method in class netkit.util.NetKitEnv

get(String, String) - Static method in class netkit.util.NetKitEnv

getAccuracy() - Method in class netkit.util.ConfusionMatrix

getAccuracy(int) - Method in class netkit.util.ConfusionMatrix

getAdjacencyMatrix(boolean) - Method in class netkit.util.GraphMetrics

Get the (possibly unweighted) adjacency matrix of this graph in the COLT sparseMatrix2D format.

getAllAttributes() - Method in class netkit.graph.Graph

Gets an array of Attributes containing the node types in this graph.

getAlphaCentralities() - Method in class netkit.util.ApproximateCentralities

getAlphaCentralityAlpha() - Method in class netkit.util.GraphMetrics

getAlphaCentralityDelta() - Method in class netkit.util.GraphMetrics

getAppendStatistics() - Method in class netkit.GraphStat

getApproximateCentralities() - Method in class netkit.util.GraphMetrics

getAssortativity(boolean) - Method in interface netkit.graph.edgecreator.EdgeCreator

Compute the node-based assortativity of this edge creator.

getAssortativity(boolean) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

getAssortativityMatrix(boolean) - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

getAssortativityMatrix(boolean) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

getAttribute() - Method in interface netkit.classifiers.aggregators.Aggregator

Gets the attribute that is being aggregated over.

getAttribute() - Method in class netkit.classifiers.aggregators.AggregatorImp

What is the attribute that is being aggregated

getAttribute() - Method in class netkit.classifiers.Classification

getAttribute() - Method in class netkit.classifiers.DataView

getAttribute() - Method in class netkit.classifiers.Estimate

getAttribute() - Method in class netkit.classifiers.NetworkLearning

getAttribute(String) - Method in class netkit.graph.Attributes

Get the Attribute with a particular name.

getAttribute(int) - Method in class netkit.graph.Attributes

Get the Attribute at a particular index; indexes honor the presence of a key Attribute within this container.

getAttribute() - Method in class netkit.util.HistogramCategorical

Gets the attribute associated with this histogram.

getAttribute() - Method in class netkit.util.HistogramDiscrete

Gets the attribute associated with this histogram.

getAttributeIndex(String) - Method in class netkit.classifiers.aggregators.AggregatorImp

Get the index of the attribute in the instance vector array--we need to go through a node to get at this information.

getAttributeIndex(String, Attribute) - Static method in class netkit.classifiers.aggregators.SharedNodeInfo

getAttributeIndex() - Method in class netkit.classifiers.DataView

getAttributeIndex(String) - Method in class netkit.graph.Attributes

Get the index of an attribute within this container; indexes honor the presence of a key Attribute within this container.

getAttributeIndex() - Method in interface netkit.graph.edgecreator.EdgeCreator

Which attribute is this based on.

getAttributeIndex() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

getAttributeIndex(String) - Method in class netkit.graph.Node

Get the integer index of a single value Attribute within this container.

getAttributeMetaInfo(String, Attribute) - Method in class netkit.graph.Graph

Factory method which gets the meta info object for the supplied nodeType name and attribute.

getAttributeMetaInfo(String, AttributeCategorical) - Method in class netkit.graph.Graph

Factory method which gets the meta info object for the supplied nodeType name and attribute.

getAttributeNames() - Method in class netkit.classifiers.ClassifierImp

getAttributeNames() - Method in class netkit.classifiers.relational.NetworkClassifierImp

getAttributes(String) - Method in class netkit.graph.Graph

Get the Attributes container matching the string provided.

getAttributes() - Method in class netkit.graph.Node

Get the Attributes container detailing the attributes contained within this node.

getAttributeValue() - Method in interface netkit.classifiers.aggregators.AggregatorByValue

Gets the value value that is being aggregated on (e.g., how often did 'aquavit' appear would return the double value representing 'aquavit' in an AttributeCategorical)

getAttributeValue() - Method in class netkit.classifiers.aggregators.AggregatorByValueImp

getAttributeValue() - Method in interface netkit.graph.edgecreator.EdgeCreator

Which attribute value is this based on.

getAttributeValue() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

getAUC() - Method in class netkit.util.ROC

getAverageRank(List<? extends PickLabelStrategy.LabelNode>, PickLabelStrategy.LabelNode) - Method in class netkit.classifiers.active.PickLabelStrategyImp

getAverageRank(List<? extends PickLabelStrategy.LabelNode>, int) - Method in class netkit.classifiers.active.PickLabelStrategyImp

getBaseAccuracy() - Method in class netkit.classifiers.Classification

getBaseError() - Method in class netkit.classifiers.Classification

getBeta() - Method in class netkit.inference.RelaxationLabeling

getBeta0() - Method in class netkit.inference.RelaxationLabeling

getBetweennessCentrality(Node) - Method in class netkit.util.GraphMetrics

Get the betweenness centrality for the given node.

getBinomialConfidenceInterval(double, int, double) - Static method in class netkit.util.StatUtil

getBoolean(String) - Method in class netkit.util.Configuration

getBoolean(String, boolean) - Method in class netkit.util.Configuration

getBoolean(String) - Static method in class netkit.util.NetKitEnv

getBoolean(String, boolean) - Static method in class netkit.util.NetKitEnv

getBundle(String) - Static method in class netkit.util.NetKitEnv

getCalcAssort() - Method in class netkit.GraphStat

getCentralities() - Method in class netkit.util.ApproximateCentralities

getCentrality(Node) - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

Get the centrality for the given node.

getCentrality(int) - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

Get the centrality for the given node.

getCharacteristicPathLength() - Method in class netkit.util.GraphMetrics

getChildCluster1() - Method in class netkit.util.ModularityClusterer.Cluster

getChildCluster2() - Method in class netkit.util.ModularityClusterer.Cluster

getClassDistribution() - Method in class netkit.classifiers.Classification

getClassDistribution() - Method in class netkit.classifiers.DataSplit

getClassDistribution() - Method in class netkit.classifiers.DataView

getClassification(Node) - Method in class netkit.classifiers.Estimate

getClassificationIdx(Node, int) - Method in class netkit.classifiers.Estimate

getClassifierNames() - Method in class netkit.classifiers.nonrelational.LocalMetaClassifier

getClassifierNames() - Method in class netkit.classifiers.relational.NetworkMetaClassifier

Returns the list of classifier names in the format: "RC[relational_classifiers] LC[nonrelational_classifiers]" where the list of classifiers is comma-separated and appear exactly is it was in the configuration object that was used to configure this classifier.

getClassName(String) - Method in class netkit.util.Factory

getClassPrior() - Method in class netkit.classifiers.NetworkLearning

getClassReferenceVector(AttributeCategorical, int, List<EdgeType>, boolean) - Method in class netkit.graph.AttributeCategoricalMetaInfo

Get the class reference vector from the graph for this attribute.

getClassReferenceVector(AttributeCategorical, int, AttributeCategorical, List<EdgeType>, boolean) - Method in class netkit.graph.Graph

Gets a class reference vector for the supplied parameters; returns a histogram on the results.

getClassValue(Node) - Method in class netkit.classifiers.Classification

getClosenessCentrality(Node) - Method in class netkit.util.GraphMetrics

Get the closeness centrality for the given node.

getCluster(Node) - Method in class netkit.util.GraphMetrics

getCluster(int) - Method in class netkit.util.GraphMetrics

getClusterer() - Method in class netkit.util.GraphMetrics

getCommandLines() - Static method in class netkit.classifiers.NetworkLearning

getCommandLines() - Static method in class netkit.EdgeTransformer

getCommandLines() - Static method in class netkit.GraphStat

getComponent(Node) - Method in class netkit.util.GraphMetrics

getComponentSize(int) - Method in class netkit.util.GraphMetrics

getConfig(String) - Method in class netkit.util.Factory

getConfiguration(ResourceBundle, String) - Static method in class netkit.util.Configuration

getConnectedClusterNodeSets() - Method in class netkit.util.ModularityClusterer

getConnectedClusters() - Method in class netkit.util.ModularityClusterer

getCorrelation(double[], double[]) - Static method in class netkit.util.StatUtil

getCount() - Method in class netkit.util.ConfusionMatrix

getCount(int) - Method in class netkit.util.ConfusionMatrix

getCount(int, int) - Method in class netkit.util.ConfusionMatrix

getCount(int) - Method in class netkit.util.Histogram

Gets the number of times a particular value appears in this histogram.

getCount(String) - Method in class netkit.util.HistogramCategorical

Gets the number of times a particular categorical token appears in this histogram.

getCovariance(double[], double[]) - Static method in class netkit.util.StatUtil

getCurrentAccuracy() - Method in class netkit.inference.InferenceMethod

getCurrentEstimate() - Method in class netkit.inference.GibbsSampling

getCurrentEstimate() - Method in class netkit.inference.InferenceMethod

getCurrentTrainingLOOAccuracy(NetworkClassifier) - Method in class netkit.inference.InferenceMethod

What is the accuracy on the training data, if we do a leave-one-out estimation, keeping current predictions for the test set.

getDataView() - Method in class netkit.classifiers.NetworkLearning

getDecay() - Method in class netkit.inference.RelaxationLabeling

getDefaultConfiguration() - Method in class netkit.classifiers.active.EmpiricalRiskMinimization

getDefaultConfiguration() - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

getDefaultConfiguration() - Method in class netkit.classifiers.active.ERMHybrid

getDefaultConfiguration() - Method in class netkit.classifiers.active.GraphCentralityLabeling

getDefaultConfiguration() - Method in class netkit.classifiers.active.GreedyTruth

getDefaultConfiguration() - Method in class netkit.classifiers.active.PickLabelStrategyImp

getDefaultConfiguration() - Method in class netkit.classifiers.active.UncertaintyLabeling

getDefaultConfiguration() - Method in class netkit.classifiers.ClassifierImp

getDefaultConfiguration() - Method in class netkit.classifiers.NetworkLearning

getDefaultConfiguration() - Method in class netkit.classifiers.nonrelational.ExternalPrior

Sets a default configuration where the reader is of type 'rainbow', which should resolve to the ReadEstimateRainbow class in the 'readestimate.properties' file.

getDefaultConfiguration() - Method in class netkit.classifiers.nonrelational.LocalMetaClassifier

Default configuration uses only the naive Bayes classifier in addition to any defaults from the superclass

getDefaultConfiguration() - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

Get the detault configuration of using a cosine distance function, and aggregating only on the class attribute using the ratio aggregator.

getDefaultConfiguration() - Method in class netkit.classifiers.relational.NetworkClassifierImp

Default configuration for relational learners.

getDefaultConfiguration() - Method in class netkit.classifiers.relational.NetworkMetaClassifier

Get the detault configuration of using a naive Bayes classifier both as the single non-relational and the single relational classifier..

getDefaultConfiguration() - Method in class netkit.classifiers.relational.NetworkOnlyBayes

Create a default configuration for this classifier.

getDefaultConfiguration() - Method in class netkit.classifiers.relational.ProbRelationalNeighbor

getDefaultConfiguration() - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

Creates and returns a default configuration, which only includes the laplaceonce, laplace and lfactor properties (the only ones used in this classifier as nothing else is not configurable).

getDefaultConfiguration() - Method in class netkit.inference.GibbsSampling

getDefaultConfiguration() - Method in class netkit.inference.InferenceMethod

getDefaultConfiguration() - Method in class netkit.inference.IterativeClassification

getDefaultConfiguration() - Method in class netkit.inference.NullInference

getDefaultConfiguration() - Method in class netkit.inference.RelaxationLabeling

getDefaultConfiguration() - Method in interface netkit.util.Configurable

getDegreeDistribution() - Method in class netkit.util.GraphMetrics

Return the histogram of (unweighted) edge degrees for nodes in the graph.

getDegreeOutput() - Method in class netkit.GraphStat

getDescription() - Method in class netkit.classifiers.active.ComparatorLabeler

getDescription() - Method in class netkit.classifiers.active.EmpiricalRiskMinimization

getDescription() - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

getDescription() - Method in class netkit.classifiers.active.ERMHybrid

getDescription() - Method in class netkit.classifiers.active.GraphCentralityLabeling

getDescription() - Method in class netkit.classifiers.active.GreedyTruth

getDescription() - Method in interface netkit.classifiers.active.PickLabelStrategy

getDescription() - Method in class netkit.classifiers.active.RandomLabeling

getDescription() - Method in class netkit.classifiers.active.UncertaintyLabeling

getDescription() - Method in interface netkit.classifiers.Classifier

getDescription() - Method in class netkit.classifiers.nonrelational.ClassPrior

getDescription() - Method in class netkit.classifiers.nonrelational.ExternalPrior

getDescription() - Method in class netkit.classifiers.nonrelational.LocalWeka

getDescription() - Method in class netkit.classifiers.nonrelational.MetaMultiplicative

getDescription() - Method in class netkit.classifiers.nonrelational.NullPrior

getDescription() - Method in class netkit.classifiers.nonrelational.UniformPrior

getDescription() - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

getDescription() - Method in class netkit.classifiers.relational.Harmonic

getDescription() - Method in class netkit.classifiers.relational.MetaMultiplicative

getDescription() - Method in class netkit.classifiers.relational.NetworkOnlyBayes

getDescription() - Method in class netkit.classifiers.relational.NetworkWeka

getDescription() - Method in class netkit.classifiers.relational.ProbRelationalNeighbor

getDescription() - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

getDescription() - Method in class netkit.inference.GibbsSampling

getDescription() - Method in class netkit.inference.InferenceMethod

getDescription() - Method in class netkit.inference.IterativeClassification

getDescription() - Method in class netkit.inference.NullInference

getDescription() - Method in class netkit.inference.RelaxationLabeling

getDest() - Method in class netkit.graph.Edge

Get the destination node of this object.

getDestinationNodeType(String) - Static method in class netkit.classifiers.aggregators.SharedNodeInfo

Helper function to get the node type at the other end of the given edgeType

getDestType() - Method in class netkit.graph.EdgeType

Get the destination type of this object.

getDiagonal() - Method in class netkit.util.Matrix

getDist(Node, Node) - Method in class netkit.util.GraphMetrics

getDistribution() - Method in class netkit.classifiers.DataSampler

getDistribution() - Method in class netkit.util.Histogram

Gets the distribution of values of this histogram, in no particular order.

getDoAlphaCentralities() - Method in class netkit.GraphStat

getDoCentralities() - Method in class netkit.GraphStat

getDoClustering() - Method in class netkit.GraphStat

getDoCoefficients() - Method in class netkit.GraphStat

getDoDegree() - Method in class netkit.GraphStat

getDoPagerank() - Method in class netkit.GraphStat

getDouble(String) - Method in class netkit.util.Configuration

getDouble(String, double) - Method in class netkit.util.Configuration

getDouble(String) - Static method in class netkit.util.NetKitEnv

getDouble(String, double) - Static method in class netkit.util.NetKitEnv

getEdge(String, Node, Node) - Method in class netkit.graph.Graph

Gets the edge connecting two nodes in the graph; if the nodes aren't connected return null.

getEdge(String, Node) - Method in class netkit.graph.Node

Gets the edge connecting this node to a neighbor node.

getEdgeCreators() - Method in class netkit.classifiers.NetworkLearning

getEdges() - Method in class netkit.graph.Graph

Gets all of the edges in the graph, irrespective of the EdgeType; the order is unspecified.

getEdges(EdgeType) - Method in class netkit.graph.Graph

Gets all the of the edges in the graph having a particular EdgeType; the order is unspecified.

getEdges(String) - Method in class netkit.graph.Graph

Gets all the of the edges in the graph having a particular EdgeType; the order is unspecified.

getEdges() - Method in class netkit.graph.Node

Get all the edges of this Node irrespective of EdgeType; the order is unspecified.

getEdgesByType(String) - Method in class netkit.graph.Node

Get the Edges of this Node whose EdgeType name is the supplied parameter; the order is unspecified.

getEdgesByType(String, NodeFilter) - Method in class netkit.graph.Node

Get the Edges of this Node whose EdgeType name is the supplied parameter and whose destination Nodes match the supplied NodeFilter; the order is unspecified.

getEdgesToNearestNeighbors(Node) - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

getEdgesToNearestNeighbors(Node) - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

getEdgesToNearestNeighbors(Node) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

Get the edges to the K nearest nodes (highest weight using this edge creator), where max-k was provided during initialization.

getEdgesToNeighbor(Node) - Method in class netkit.graph.Node

Get all the edges of this Node whose destination Node is the supplied node; the order is unspecified.

getEdgesToNeighbor(String) - Method in class netkit.graph.Node

Get all the edges of this Node whose destination Node is of the supplied type; the order is unspecified.

getEdgesToNeighbor(String, NodeFilter) - Method in class netkit.graph.Node

Get all the edges of this Node whose destination Node is of the supplied type and which matches the supplied NodeFilter; the order is unspecified.

getEdgeType() - Method in interface netkit.classifiers.aggregators.Aggregator

Gets the edge that is used for aggregation.

getEdgeType() - Method in class netkit.classifiers.aggregators.AggregatorImp

What is the relation that should be used to get at the neighbors of an instance

getEdgeType() - Method in class netkit.graph.Edge

Get the edge type of this object.

getEdgeType() - Method in interface netkit.graph.edgecreator.EdgeCreator

getEdgeType() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

getEdgeType(String) - Method in class netkit.graph.Graph

Get the EdgeType matching the provided edge type name.

getEdgeTypeNames() - Method in class netkit.graph.Graph

Gets an array of String containing the list of names of all EdgeTypes.

getEdgeTypeNames(String) - Method in class netkit.graph.Graph

Gets an array of String containing the list of names of the EdgeTypes whose source node type is the supplied parameter.

getEdgeTypeNames(String, String) - Method in class netkit.graph.Graph

Gets an array of String containing the list of names of the EdgeTypes whose source and destination node types are the supplied parameters.

getEdgeTypes(String) - Method in class netkit.graph.Graph

Gets an array of EdgeTypes containing the list of the EdgeTypes whose source node type is the supplied parameter.

getEdgeTypes(String, String) - Method in class netkit.graph.Graph

Gets an array of EdgeType containing the list of EdgeTypes whose source and destination node types are the supplied parameters.

getEdgeTypes() - Method in class netkit.graph.Graph

Gets an array of EdgeType containing the list of EdgeTypes in this graph.

getEfficiency() - Method in class netkit.util.GraphMetrics

Not implemented yet.

getEmpiricalRisk(Node) - Method in interface netkit.classifiers.IncrementalAssessment

What is the empirical risk if this node is labeled (after the initial model has been induced)?

getERM(Node) - Method in class netkit.classifiers.relational.Harmonic

getERM(Node, Classification) - Method in class netkit.classifiers.relational.Harmonic

getErr() - Method in class netkit.util.ConfusionMatrix

getError(int) - Method in class netkit.util.ConfusionMatrix

getEstimate(Node) - Method in class netkit.classifiers.Estimate

getEstimate(Node, double[]) - Method in class netkit.classifiers.Estimate

getFieldName() - Method in class netkit.graph.AbstractAttributeMetaInfo

Get the field name for the Attribute used for this object.

getFloat(String) - Static method in class netkit.util.NetKitEnv

getFloat(String, float) - Static method in class netkit.util.NetKitEnv

getGlobalClusterCoeff() - Method in class netkit.util.GraphMetrics

getGlobalOutput() - Method in class netkit.GraphStat

getGraph() - Method in class netkit.classifiers.Classification

getGraph() - Method in class netkit.classifiers.DataView

getGraph() - Method in class netkit.classifiers.Estimate

getGraph() - Method in class netkit.classifiers.NetworkLearner

getGraph() - Method in class netkit.classifiers.NetworkLearning

getGraph() - Method in class netkit.util.GraphView

getGraph() - Method in class netkit.util.ModularityClusterer

getGraphCentrality() - Method in class netkit.util.GraphMetrics

Get the graph centrality.

getGraphCentrality(Node) - Method in class netkit.util.GraphMetrics

Get the graph centrality for a specific node.

getGraphDensity() - Method in class netkit.util.GraphMetrics

Return the density of the graph as defined by: |E|/(|N|*(|N)-1)), where |E| is the number of edges and |N| is the number of nodes in the graph.

getHarmonicFunction() - Method in class netkit.classifiers.active.GraphCentralityLabeling

getHistogram(Node) - Method in class netkit.classifiers.aggregators.SharedNodeInfo

Get the histogram of observed values (of the neighbors of the source node) of the discrete attribute that is being aggregated over.

getId() - Method in class netkit.util.ModularityClusterer.Cluster

getIncrementalAccuracy(Node, Classification) - Method in interface netkit.classifiers.IncrementalAssessment

What would be the new accuracy if this node is labeled (after the initial model has been induced)?

getIndex() - Method in class netkit.graph.Node

Get the index of this node.

getInferenceMethod() - Method in class netkit.classifiers.NetworkLearner

getInfo(String, int, EdgeType) - Static method in class netkit.classifiers.aggregators.SharedNodeInfo

Get a SharedNodeInfo instance for a given node type, attribute and edge type.

getInformationCentrality(Node) - Method in class netkit.util.GraphMetrics

Not implemented yet.

getInitialPrior() - Method in class netkit.inference.InferenceMethod

getInput() - Method in class netkit.EdgeTransformer

getInstance(String, String, double) - Static method in class netkit.classifiers.active.GraphCentralityLabeling

getInstance() - Static method in class netkit.classifiers.aggregators.AggregatorFactory

Getter method to get the singleton AggregatorFactory class.

getInt(String) - Method in class netkit.util.Configuration

return (int)-1 if no such value exists.

getInt(String, int) - Method in class netkit.util.Configuration

getInt(String) - Static method in class netkit.util.NetKitEnv

getInt(String, int) - Static method in class netkit.util.NetKitEnv

getIsolatedClusterNodeSets() - Method in class netkit.util.ModularityClusterer

getIsolatedClusters() - Method in class netkit.util.ModularityClusterer

getIterationNum() - Method in class netkit.classifiers.active.PickLabelStrategyImp

getKey() - Method in class netkit.graph.Attributes

Get the key Attribute from this container.

getKeyIndex() - Method in class netkit.graph.Attributes

Get the key index from this container.

getKnown() - Method in class netkit.classifiers.NetworkLearning

getLabeledNodes(DataSplit, boolean) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

Get a classification object which contains all the nodes to be used to calculate assortativity

getLabels() - Method in class netkit.classifiers.active.GraphCentralityLabeling

getLearner() - Method in class netkit.classifiers.NetworkLearning

getLocalClassifier() - Method in class netkit.classifiers.NetworkLearner

getLocalClusterCoeff() - Method in class netkit.util.GraphMetrics

getLogger() - Method in interface netkit.classifiers.Classifier

getLogger() - Method in class netkit.classifiers.ClassifierImp

getLogger(String) - Static method in class netkit.util.NetKitEnv

getLogger(Object) - Static method in class netkit.util.NetKitEnv

getLong(String) - Method in class netkit.util.Configuration

return (int)-1 if no such value exists.

getLong(String, long) - Method in class netkit.util.Configuration

getLong(String) - Static method in class netkit.util.NetKitEnv

getLong(String, long) - Static method in class netkit.util.NetKitEnv

getMajorityClass() - Method in class netkit.classifiers.Classification

getMatrix() - Method in class netkit.util.Matrix

getMax(Node) - Method in class netkit.classifiers.aggregators.SharedNodeInfo

Get the maximum observed value (of the neighbors of the source node) of the discrete or continuous attribute that is being aggregated over.

getMax() - Method in class netkit.graph.AbstractAttributeMetaInfo

Get the maximum value this Graph has for this field.

getMaxComponentIdx() - Method in class netkit.util.GraphMetrics

getMaxComponentSize() - Method in class netkit.util.GraphMetrics

getMaxDegree() - Method in class netkit.util.GraphMetrics

getMaxDist() - Method in class netkit.util.GraphMetrics

getMaxEdges() - Method in interface netkit.graph.edgecreator.EdgeCreator

How many edges should there be at maximum per node?

getMaxEdges() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

getMaxEdgeWeight() - Method in class netkit.util.GraphMetrics

getMaxIdx(double[]) - Static method in class netkit.util.VectorMath

getMaxIdx(int[]) - Static method in class netkit.util.VectorMath

getMaxValue() - Method in class netkit.util.HistogramDiscrete

Gets the maximum value stored in this object.

getMaxValue(double[]) - Static method in class netkit.util.VectorMath

getMaxValue(int[]) - Static method in class netkit.util.VectorMath

getMaxWeightedDegree() - Method in class netkit.util.GraphMetrics

getMean(Node) - Method in class netkit.classifiers.aggregators.SharedNodeInfo

Get the mean observed value (of the neighbors of the source node) of the discrete or continuous attribute that is being aggregated over.

getMean() - Method in class netkit.graph.AbstractAttributeMetaInfo

Get the mean value this Graph has for this field.

getMean(double[]) - Static method in class netkit.util.StatUtil

getMeanDegree() - Method in class netkit.util.GraphMetrics

getMeanDist() - Method in class netkit.util.GraphMetrics

getMeanEdgeWeight() - Method in class netkit.util.GraphMetrics

getMeanValue() - Method in class netkit.util.HistogramDiscrete

Gets the mean (average) value of the values in this object.

getMeanWeightedDegree() - Method in class netkit.util.GraphMetrics

getMedian() - Method in class netkit.graph.AbstractAttributeMetaInfo

Get the median value this Graph has for this field.

getMedianValue() - Method in class netkit.util.HistogramDiscrete

Gets the median value of the values in this object.

getMetrics() - Method in class netkit.classifiers.active.GraphCentralityLabeling

getMetrics() - Method in class netkit.graph.Graph

Get the metrics encapsulating statistics about this graph.

getMin(Node) - Method in class netkit.classifiers.aggregators.SharedNodeInfo

Get the minium observed value (of the neighbors of the source node) of the discrete or continuous attribute that is being aggregated over.

getMin() - Method in class netkit.graph.AbstractAttributeMetaInfo

Get the minimum value this Graph has for this field.

getMinDegree() - Method in class netkit.util.GraphMetrics

getMinEdgeWeight() - Method in class netkit.util.GraphMetrics

getMinIdx(double[]) - Static method in class netkit.util.VectorMath

getMinIdx(int[]) - Static method in class netkit.util.VectorMath

getMinK() - Method in class netkit.EdgeTransformer

getMinValue() - Method in class netkit.util.HistogramDiscrete

Gets the minimum value stored in this object.

getMinValue(double[]) - Static method in class netkit.util.VectorMath

getMinValue(int[]) - Static method in class netkit.util.VectorMath

getMinWeightedDegree() - Method in class netkit.util.GraphMetrics

getMode() - Method in class netkit.graph.AttributeCategoricalMetaInfo

Get the mode value this Graph has for this field.

getMode() - Method in class netkit.util.Histogram

Gets the "mode" for this set of values.

getName() - Method in class netkit.classifiers.active.ComparatorLabeler

getName() - Method in class netkit.classifiers.active.EmpiricalRiskMinimization

getName() - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

getName() - Method in class netkit.classifiers.active.ERMHybrid

getName() - Method in class netkit.classifiers.active.GraphCentralityLabeling

getName() - Method in class netkit.classifiers.active.GreedyTruth

getName() - Method in interface netkit.classifiers.active.PickLabelStrategy

getName() - Method in class netkit.classifiers.active.RandomLabeling

getName() - Method in class netkit.classifiers.active.UncertaintyLabeling

getName() - Method in interface netkit.classifiers.aggregators.Aggregator

Gets the name of the field represented by this object.

getName() - Method in class netkit.classifiers.aggregators.AggregatorImp

getName() - Method in interface netkit.classifiers.Classifier

getName() - Method in class netkit.classifiers.nonrelational.ClassPrior

getName() - Method in class netkit.classifiers.nonrelational.ExternalPrior

getName() - Method in class netkit.classifiers.nonrelational.LocalWeka

getName() - Method in class netkit.classifiers.nonrelational.MetaMultiplicative

getName() - Method in class netkit.classifiers.nonrelational.NullPrior

getName() - Method in class netkit.classifiers.nonrelational.UniformPrior

getName() - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

getName() - Method in class netkit.classifiers.relational.Harmonic

getName() - Method in class netkit.classifiers.relational.MetaMultiplicative

getName() - Method in class netkit.classifiers.relational.NetworkOnlyBayes

getName() - Method in class netkit.classifiers.relational.NetworkWeka

getName() - Method in class netkit.classifiers.relational.ProbRelationalNeighbor

getName() - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

getName() - Method in class netkit.graph.Attribute

Get the name of this Attribute.

getName() - Method in class netkit.graph.Attributes

Get the name of this object.

getName() - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

getName() - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

getName() - Method in class netkit.graph.edgecreator.BayesCategoricalEdgeCreator

getName() - Method in class netkit.graph.edgecreator.CosineDistanceEdgeCreator

getName() - Method in interface netkit.graph.edgecreator.EdgeCreator

The name of this edge-creator

getName() - Method in class netkit.graph.edgecreator.EuclideanDistanceEdgeCreator

getName() - Method in class netkit.graph.edgecreator.GaussianNumericEdgeCreator

getName() - Method in class netkit.graph.edgecreator.MahalanobisDistanceEdgeCreator

getName() - Method in class netkit.graph.edgecreator.NormalizedNumericEdgeCreator

getName() - Method in class netkit.graph.EdgeType

Get the name of this object.

getName() - Method in class netkit.graph.Node

Get the name of this node.

getName() - Method in class netkit.inference.GibbsSampling

getName() - Method in class netkit.inference.InferenceMethod

getName() - Method in class netkit.inference.IterativeClassification

getName() - Method in class netkit.inference.NullInference

getName() - Method in class netkit.inference.RelaxationLabeling

getNeighbors() - Method in class netkit.graph.Node

Gets the adjacent nodes connected to this node irrespective of the EdgeType; the order is unspecified.

getNeighbors(String) - Method in class netkit.graph.Node

Gets the adjacent nodes connected to this node through an Edge with the supplied EdgeType name; the order is unspecified.

getNeighbors(List<EdgeType>, NodeFilter) - Method in class netkit.graph.Node

Gets a List of Edges to neighboring Nodes based on the supplied EdgeType path.

getNeighbors(List<EdgeType>) - Method in class netkit.graph.Node

Same as Node.getNeighbors(List,NodeFilter) except that the NodeFilter always accepts Nodes, nothing is filtered out.

getNetworkClassifier() - Method in class netkit.classifiers.NetworkLearner

getNetworkLearner() - Method in class netkit.classifiers.active.PickLabelStrategyImp

getNode(int) - Method in class netkit.graph.Graph

Gets the node corresponding to the supplied int index.

getNode(String, String) - Method in class netkit.graph.Graph

Gets the node coresponding to the supplied node name and node type.

getNode() - Method in class netkit.util.ModularityClusterer.Cluster

getNodeIndex(Node) - Method in class netkit.util.GraphMetrics

getNodeInfo(Node) - Method in class netkit.classifiers.aggregators.AggregatorImp

This is cached aggregation information about the node as is relevant to the relationship that this aggregator uses.

getNodeOutput() - Method in class netkit.GraphStat

getNodes() - Method in class netkit.graph.Graph

Gets all of the nodes in the graph; the order is unspecified.

getNodes(String) - Method in class netkit.graph.Graph

Gets all of the Nodes matching the supplied node type.

getNodes(String, NodeFilter) - Method in class netkit.graph.Graph

Gets all of the Nodes matching the supplied node type and which also are accepted by the supplied NodeFilter.

getNodes(Attributes) - Method in class netkit.graph.Graph

Gets all of the Nodes whose Attributes container matches the supplied parameter.

getNodeStatistics(GraphMetrics, Node) - Static method in class netkit.graph.io.NetkitGraph

getNodeStatNames(GraphMetrics) - Static method in class netkit.graph.io.NetkitGraph

getNodesToLabel(DataSplit, Estimate, int) - Method in interface netkit.classifiers.active.PickLabelStrategy

Get the list of nodes to get labels for.

getNodesToLabel(DataSplit, Estimate, int) - Method in class netkit.classifiers.active.PickLabelStrategyImp

Get the list of nodes to get labels for.

getNodeType() - Method in class netkit.classifiers.Classification

getNodeType() - Method in class netkit.classifiers.DataView

getNodeType() - Method in class netkit.classifiers.Estimate

getNodeType() - Method in class netkit.classifiers.NetworkLearning

getNodeTypeName() - Method in class netkit.graph.AbstractAttributeMetaInfo

Get the nodeTypeName for the Attributes container used for this object.

getNodeTypes() - Method in class netkit.graph.Graph

Gets an array of String containing the list of names of the node types in this graph.

getNofifyListeners() - Method in interface netkit.classifiers.Classifier

getNofifyListeners() - Method in class netkit.classifiers.ClassifierImp

getNofifyListeners() - Method in class netkit.inference.InferenceMethod

getNumClusterNodes() - Method in class netkit.util.ModularityClusterer

getNumClusters() - Method in class netkit.util.GraphMetrics

getNumComponents() - Method in class netkit.util.GraphMetrics

getNumConnectedClusters() - Method in class netkit.util.ModularityClusterer

getNumEdges() - Method in class netkit.util.GraphMetrics

getNumIsolatedClusters() - Method in class netkit.util.ModularityClusterer

getNumIterations() - Method in class netkit.inference.InferenceMethod

getNumNeg() - Method in class netkit.util.ROC

getNumNodes() - Method in class netkit.util.GraphMetrics

getNumPath2() - Method in class netkit.util.GraphMetrics

getNumPos() - Method in class netkit.util.ROC

getNumSingletons() - Method in class netkit.util.GraphMetrics

getNumSingletons() - Method in class netkit.util.ModularityClusterer

getNumtriangles() - Method in class netkit.util.GraphMetrics

getOneSidedZ(int, double) - Static method in class netkit.util.StatUtil

getOutput() - Method in class netkit.EdgeTransformer

getOutput() - Method in class netkit.GraphStat

getOutputFormat() - Method in class netkit.classifiers.io.PrintEstimateWriter

getOutputFormat() - Method in class netkit.classifiers.NetworkLearning

getPagerankAlpha() - Method in class netkit.util.GraphMetrics

getPagerankCentralities() - Method in class netkit.util.ApproximateCentralities

getPagerankDelta() - Method in class netkit.util.GraphMetrics

getPajekColor() - Method in class netkit.GraphStat

getPajekColorStr() - Method in class netkit.GraphStat

getPajekLabel() - Method in class netkit.GraphStat

getParent() - Method in class netkit.util.Configuration

getParserCOMMA(int) - Static method in class netkit.graph.io.SplitParser

Gets a parser that parses lines containing comma separated values, no whitespace allowed.

getParserCOMMAWS(int) - Static method in class netkit.graph.io.SplitParser

Gets a parser that parses lines containing comma separated values, possibly surrounded with whitespace; whitespace is ignored/removed.

getParserCSV(int) - Static method in class netkit.graph.io.SplitParser

Gets a parser that parses lines containing comma separated values possibly wrapped with double quotes, possibly surrounded with whitespace.

getParserWS(int) - Static method in class netkit.graph.io.SplitParser

Gets a parser that parses lines containing whitespace separated values, with arbitrary extra whitespace between values.

getParserWS1(int) - Static method in class netkit.graph.io.SplitParser

Gets a parser that parses lines containing whitespace separated values, separators are exactly one character and no extra whitespace appears anywhere in the supplied lines.

getPaths(String, String, int) - Method in class netkit.graph.Graph

Gets all paths in this Graph from the supplied source node type to the supplied destination node type that fit within the supplied maximum length.

getPoints() - Method in class netkit.util.ROC

getPrintWriter(String) - Static method in class netkit.util.NetKitEnv

getPrior() - Method in class netkit.classifiers.DataSplit

getPrior() - Method in class netkit.classifiers.DataView

getPruneLess() - Method in class netkit.EdgeTransformer

getPruneMore() - Method in class netkit.EdgeTransformer

getPruneSingletons() - Method in class netkit.GraphStat

getRandomSeed() - Method in class netkit.classifiers.NetworkLearning

getRank(DataSplit, Estimate, Node) - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

getRank(DataSplit, Estimate, Node) - Method in class netkit.classifiers.active.GraphCentralityLabeling

getRank(DataSplit, Estimate, Node) - Method in class netkit.classifiers.active.GreedyTruth

getRank(DataSplit, Estimate, Node) - Method in interface netkit.classifiers.active.PickLabelStrategy

Get the rank of the given node if the strategy were to pick the node.

getRank(DataSplit, Estimate, Node) - Method in class netkit.classifiers.active.PickLabelStrategyImp

getRank(DataSplit, Estimate, Node) - Method in class netkit.classifiers.active.UncertaintyLabeling

getRegex() - Method in class netkit.graph.io.SplitParser

Gets a String representation of the regular expression defined for the Matcher object used on each line.

getReverse() - Method in class netkit.EdgeTransformer

getReweight() - Method in class netkit.EdgeTransformer

getRoot() - Method in class netkit.util.Configuration

getSaveAttributes() - Method in class netkit.GraphStat

getSaveClusterStem() - Method in class netkit.GraphStat

getSaveComponentStem() - Method in class netkit.GraphStat

getSaveDot() - Method in class netkit.GraphStat

getSaveGraphStem() - Method in class netkit.GraphStat

getSaveNetkit() - Method in class netkit.GraphStat

getSavePajek() - Method in class netkit.GraphStat

getScore(Node, int) - Method in class netkit.classifiers.Estimate

getSeed() - Static method in class netkit.util.VectorMath

getSet() - Method in class netkit.util.Histogram

Gets the set of value->count pairs in this histogram.

getShortName() - Method in class netkit.classifiers.active.ComparatorLabeler

getShortName() - Method in class netkit.classifiers.active.EmpiricalRiskMinimization

getShortName() - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

getShortName() - Method in class netkit.classifiers.active.ERMHybrid

getShortName() - Method in class netkit.classifiers.active.GraphCentralityLabeling

getShortName() - Method in class netkit.classifiers.active.GreedyTruth

getShortName() - Method in interface netkit.classifiers.active.PickLabelStrategy

getShortName() - Method in class netkit.classifiers.active.RandomLabeling

getShortName() - Method in class netkit.classifiers.active.UncertaintyLabeling

getShortName() - Method in interface netkit.classifiers.Classifier

getShortName() - Method in class netkit.classifiers.nonrelational.ClassPrior

getShortName() - Method in class netkit.classifiers.nonrelational.ExternalPrior

getShortName() - Method in class netkit.classifiers.nonrelational.LocalWeka

getShortName() - Method in class netkit.classifiers.nonrelational.MetaMultiplicative

getShortName() - Method in class netkit.classifiers.nonrelational.NullPrior

getShortName() - Method in class netkit.classifiers.nonrelational.UniformPrior

getShortName() - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

getShortName() - Method in class netkit.classifiers.relational.Harmonic

getShortName() - Method in class netkit.classifiers.relational.MetaMultiplicative

getShortName() - Method in class netkit.classifiers.relational.NetworkOnlyBayes

getShortName() - Method in class netkit.classifiers.relational.NetworkWeka

getShortName() - Method in class netkit.classifiers.relational.ProbRelationalNeighbor

getShortName() - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

getShortName() - Method in class netkit.inference.GibbsSampling

getShortName() - Method in class netkit.inference.InferenceMethod

getShortName() - Method in class netkit.inference.IterativeClassification

getShortName() - Method in class netkit.inference.NullInference

getShortName() - Method in class netkit.inference.RelaxationLabeling

getSignificance(int, double) - Static method in class netkit.util.StatUtil

getSignificanceDifference(double, int, double, int) - Static method in class netkit.util.StatUtil

Return: 1-sided confidence that err1 < err2 (0 if not significant)

getSize() - Method in class netkit.util.ModularityClusterer.Cluster

getSource() - Method in class netkit.graph.Edge

Get the source node of this object.

getSourceType() - Method in class netkit.graph.EdgeType

Get the source type of this object.

getSplit() - Method in class netkit.classifiers.active.PickLabelStrategyImp

getSplit(Classification) - Method in class netkit.classifiers.DataView

getSplit(Classification, Classification) - Method in class netkit.classifiers.DataView

getSplit(NodeFilter) - Method in class netkit.classifiers.DataView

getSplit(int) - Method in class netkit.classifiers.DataView

getSplit(int, int) - Method in class netkit.classifiers.DataView

getSplit(double) - Method in class netkit.classifiers.DataView

getSplit(double, double) - Method in class netkit.classifiers.DataView

getSplit() - Method in class netkit.classifiers.NetworkLearner

getSplits(int, double, double) - Method in class netkit.classifiers.DataView

getSplits(int, int, int) - Method in class netkit.classifiers.DataView

getSplits(int, double) - Method in class netkit.classifiers.DataView

getSplits(int, int) - Method in class netkit.classifiers.DataView

getSplits() - Method in class netkit.classifiers.NetworkLearning

getStdDev(double[], double) - Static method in class netkit.util.StatUtil

getStdOut() - Static method in class netkit.util.NetKitEnv

getSum(Node, Estimate) - Method in class netkit.classifiers.aggregators.SharedNodeInfo

Get the (weighted) sum of all relevant neighbors.

getTest() - Method in class netkit.classifiers.NetworkLearning

getTestSet() - Method in class netkit.classifiers.DataSplit

getTestSetSize() - Method in class netkit.classifiers.DataSplit

getToken(int) - Method in class netkit.graph.AttributeCategorical

Gets the i'th token from the list of valid tokens for this categorical attribute; the index is a zero-based array lookup.

getToken(int) - Method in class netkit.graph.TokenSet

Gets the i'th element from the array of valid tokens.

getTokens() - Method in class netkit.graph.AttributeCategorical

Gets the tokens valid for this categorical attribute.

getTokens() - Method in class netkit.graph.TokenSet

Get a String array of valid tokens.

getTopK() - Method in class netkit.EdgeTransformer

getTotalCount() - Method in class netkit.util.Histogram

Gets the cumulative number of times all values appear in this histogram.

getTotalEdgeWeights() - Method in class netkit.util.GraphMetrics

getTrainSet() - Method in class netkit.classifiers.DataSplit

getTrainSetSize() - Method in class netkit.classifiers.DataSplit

getTrueClassValue(Node) - Method in class netkit.classifiers.DataView

getTruth() - Method in class netkit.classifiers.DataView

getTruth() - Method in class netkit.classifiers.NetworkLearning

getTwoSidedZ(int, double) - Static method in class netkit.util.StatUtil

getType() - Method in interface netkit.classifiers.aggregators.Aggregator

Gets the Type of the value stored in this object.

getType() - Method in class netkit.classifiers.aggregators.AggregatorImp

Gets the Type of the value stored in this object.

getType() - Method in class netkit.graph.Attribute

Get the type of this Attribute.

getType() - Method in class netkit.graph.Node

Get the type name of this node.

getUnconditionalReferenceVector(List<EdgeType>, boolean) - Method in class netkit.graph.AttributeCategoricalMetaInfo

Get the unconditional reference vector from the graph for this attribute.

getUnconditionalReferenceVector(AttributeCategorical, List<EdgeType>, boolean) - Method in class netkit.graph.Graph

Gets an unconditional reference vector for the supplied parameters; returns a histogram on the results.

getUnknownSet() - Method in class netkit.classifiers.DataSplit

getUnknownSetSize() - Method in class netkit.classifiers.DataSplit

getUnweightedDegree() - Method in class netkit.graph.Node

Get the number of outgoing Edges.

getUnweightedDegree(String) - Method in class netkit.graph.Node

Get the number of Edges which connect to a destination Node of the supplied node type.

getUnweightedDegree(EdgeType) - Method in class netkit.graph.Node

Get the number of outbound Edges of the supplied EdgeType.

getValidNames() - Method in class netkit.util.Factory

getValue(Node) - Method in interface netkit.classifiers.aggregators.Aggregator

Gets the value stored in this object for the supplied Node.

getValue(Node, Estimate) - Method in interface netkit.classifiers.aggregators.Aggregator

Gets the value stored in this object for the supplied Node.

getValue(Node) - Method in class netkit.classifiers.aggregators.AggregatorImp

Aggregate around the given node in the graph and return the result.

getValue(Node, Estimate) - Method in class netkit.classifiers.aggregators.Count

getValue(Node, Estimate) - Method in class netkit.classifiers.aggregators.Exist

getValue(Node, Estimate) - Method in class netkit.classifiers.aggregators.Max

getValue(Node, Estimate) - Method in class netkit.classifiers.aggregators.Mean

getValue(Node, Estimate) - Method in class netkit.classifiers.aggregators.Min

getValue(Node, Estimate) - Method in class netkit.classifiers.aggregators.Mode

getValue(Node, Estimate) - Method in class netkit.classifiers.aggregators.Ratio

getValue(String) - Method in class netkit.graph.AttributeCategorical

Gets the numerical value for a particular token; the token must be in the set of valid tokens for this attribute.

getValue(Node) - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

getValue(Node) - Method in class netkit.graph.edgecreator.NormalizedNumericEdgeCreator

getValue(int) - Method in class netkit.graph.Node

Get the value associated with the attribute field at the supplied index.

getValue(String) - Method in class netkit.graph.Node

Get the value associated with the named attribute field.

getValue(String) - Method in class netkit.graph.TokenSet

Gets the integer value associated with the supplied token.

getValues(String, int) - Method in class netkit.graph.Graph

Gets a double array of values from Nodes in this Graph matching the supplied node type; the values are obtained from the Attribute at the supplied index offset into the Node's fields.

getValues(String, NodeFilter, int) - Method in class netkit.graph.Graph

Gets a double array of values from Nodes in this Graph matching the supplied node type and which also are accepted by the supplied NodeFilter; the values are obtained from the Attribute at the supplied index offset into the Node's fields.

getValues(String, String) - Method in class netkit.graph.Graph

Gets a double array of values from Nodes in this Graph matching the supplied node type; the values are obtained from the Attribute matching the supplied field name.

getValues(String, NodeFilter, String) - Method in class netkit.graph.Graph

Gets a double array of values from Nodes in this Graph matching the supplied node type and which also are accepted by the supplied NodeFilter; the values are obtained from the Attribute matching the supplied field name.

getValues() - Method in class netkit.graph.Node

Gets all of the values associated with this node.

getVariance(double[], double) - Static method in class netkit.util.StatUtil

getView() - Method in class netkit.classifiers.DataSplit

getWeight() - Method in class netkit.graph.Edge

Get the weight field of this object.

getWeight(Node, Node) - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

getWeight(Node, Node) - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

getWeight(Node, Node) - Method in class netkit.graph.edgecreator.BayesCategoricalEdgeCreator

getWeight(Node, Node) - Method in class netkit.graph.edgecreator.CosineDistanceEdgeCreator

getWeight(Node, Node) - Method in interface netkit.graph.edgecreator.EdgeCreator

Calculate the edgeweight from node src to node dest.

getWeight(Node, Node) - Method in class netkit.graph.edgecreator.EuclideanDistanceEdgeCreator

getWeight(Node, Node) - Method in class netkit.graph.edgecreator.MahalanobisDistanceEdgeCreator

getWeight(Node, Node) - Method in class netkit.graph.edgecreator.NormalizedNumericEdgeCreator

getWeightedBetweennessCentrality(Node) - Method in class netkit.util.GraphMetrics

Get the betweenness centrality for the given node.

getWeightedCharacteristicPathLength() - Method in class netkit.util.GraphMetrics

getWeightedClosenessCentrality(Node) - Method in class netkit.util.GraphMetrics

Get the closeness centrality for the given node.

getWeightedDegree() - Method in class netkit.graph.Node

Get the sum of all weights of outgoing Edges.

getWeightedDegree(String) - Method in class netkit.graph.Node

Get the sum of all weights of Edges which connect to a destination Node of the supplied node type.

getWeightedDegree(EdgeType) - Method in class netkit.graph.Node

Get the sum of all weights of outbound Edges of the supplied EdgeType.

getWeightedDist(Node, Node) - Method in class netkit.util.GraphMetrics

getWeightedGraphCentrality() - Method in class netkit.util.GraphMetrics

Get the graph centrality.

getWeightedGraphCentrality(Node) - Method in class netkit.util.GraphMetrics

Get the graph centrality for a specific node.

getWeightedInformationCentrality(Node) - Method in class netkit.util.GraphMetrics

Not implemented yet.

getWeightedMaxDist() - Method in class netkit.util.GraphMetrics

getWeightedMeanDist() - Method in class netkit.util.GraphMetrics

getWeightFast(Node, Node) - Method in class netkit.graph.edgecreator.BaseNumericEdgeCreator

getWeightFast(Node, Node) - Method in class netkit.graph.edgecreator.GaussianNumericEdgeCreator

getWeightFast(Node, Node) - Method in class netkit.graph.edgecreator.NormalizedNumericEdgeCreator

getXdim() - Method in class netkit.util.Matrix

getYdim() - Method in class netkit.util.Matrix

GibbsSampling - Class in netkit.inference

GibbsSampling() - Constructor for class netkit.inference.GibbsSampling

globalInfo() - Method in class netkit.classifiers.bayes.NaiveBayesMultinomial

Returns a string describing this classifier

gm - Variable in class netkit.classifiers.active.graphfunctions.ScoringFunction

gm - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

graph - Variable in class netkit.classifiers.ClassifierImp

graph - Variable in class netkit.graph.AbstractAttributeMetaInfo

graph - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

Graph - Class in netkit.graph

This class represents the relational network in memory.

Graph() - Constructor for class netkit.graph.Graph

graph - Variable in class netkit.util.GraphMetrics

GraphCentralityLabeling - Class in netkit.classifiers.active

Graph Centrality Labeling for Active Learning iteratively picks central nodes in a graph that are in clusters that have no known labels.

GraphCentralityLabeling() - Constructor for class netkit.classifiers.active.GraphCentralityLabeling

graphHasMissingClassValues() - Method in class netkit.classifiers.DataView

GraphMetrics - Class in netkit.util

GraphMetrics(Graph) - Constructor for class netkit.util.GraphMetrics

Compute metrics over all nodes in the graph

GraphMetrics(Graph, String) - Constructor for class netkit.util.GraphMetrics

Compute certain metrics only over nodes of the given node type

GraphMetrics.AdjacencyMatrix - Class in netkit.util

This is a wrapper class for the COLT DoubleMatrix2D object such that NetKit does not require the colt library in its classpath.

GraphMetrics.AdjacencyMatrix(boolean) - Constructor for class netkit.util.GraphMetrics.AdjacencyMatrix

Create a wrapper for the (possibly unweighted) adjacency matrix of this graph in the COLT sparseMatrix2D format.

GraphStat - Class in netkit

GraphStat() - Constructor for class netkit.GraphStat

GraphStat(String[]) - Constructor for class netkit.GraphStat

graphstat - Static variable in class netkit.Netkit

GraphView - Class in netkit.util

GraphView(Graph) - Constructor for class netkit.util.GraphView

GreedyTruth - Class in netkit.classifiers.active

Picks next labels by getting the best jump in accuracy, knowing what the truth is.

GreedyTruth() - Constructor for class netkit.classifiers.active.GreedyTruth

H

Harmonic - Class in netkit.classifiers.relational

The Harmonic Function classifier from Zhu (2003) Reference: Zhu, X., Ghahramani, Z., & Lafferty, J.

Harmonic() - Constructor for class netkit.classifiers.relational.Harmonic

hashCode() - Method in class netkit.graph.Attributes

Returns a hash code value for this object.

hashCode() - Method in class netkit.graph.Edge

Returns a hash code value for this object.

hashCode() - Method in class netkit.graph.EdgeType

Returns a hash code value for this object.

hashCode() - Method in class netkit.graph.Node

Returns a hash code value for this object.

hasNext() - Method in class netkit.util.ArrayIterator

hasTruth() - Method in class netkit.classifiers.DataSplit

hideClassValue(Node) - Method in class netkit.classifiers.DataView

Histogram - Class in netkit.util

This abstract class represents a histogram on Node field values.

Histogram(double[], Attribute, int) - Constructor for class netkit.util.Histogram

This constructor creates a histogram object given an array of values and an attribute type.

Histogram(Node[], Attribute, int) - Constructor for class netkit.util.Histogram

This constructor creates a histogram object given an array of nodes and an attribute from which to get the values.

Histogram(Edge[], Attribute, int) - Constructor for class netkit.util.Histogram

This constructor creates a histogram object given an array of edges and an attribute from which to get the values.

HistogramCategorical - Class in netkit.util

This class represents a histogram on Node field values which have CATEGORICAL type.

HistogramCategorical(double[], AttributeCategorical) - Constructor for class netkit.util.HistogramCategorical

This constructor is a convenience for accepting all values without any minimum occurance.

HistogramCategorical(double[], AttributeCategorical, int) - Constructor for class netkit.util.HistogramCategorical

This constructor creates a histogram object given an array of values and an attribute type.

HistogramCategorical(Edge[], AttributeCategorical) - Constructor for class netkit.util.HistogramCategorical

This constructor is a convenience for accepting all edge values without any minimum occurance.

HistogramCategorical(Node[], AttributeCategorical) - Constructor for class netkit.util.HistogramCategorical

This constructor is a convenience for accepting all node values without any minimum occurance.

HistogramCategorical(Node[], AttributeCategorical, int) - Constructor for class netkit.util.HistogramCategorical

This constructor creates a histogram object given an array of nodes and an attribute from which to get the values.

HistogramCategorical(Edge[], AttributeCategorical, int) - Constructor for class netkit.util.HistogramCategorical

This constructor creates a histogram object given an array of edges and an attribute from which to get the values.

HistogramDiscrete - Class in netkit.util

This class represents a histogram on Node field values which have DISCRETE type.

HistogramDiscrete(double[], AttributeDiscrete) - Constructor for class netkit.util.HistogramDiscrete

This constructor is a convenience for accepting all values without any minimum occurance.

HistogramDiscrete(double[], AttributeDiscrete, int) - Constructor for class netkit.util.HistogramDiscrete

This constructor creates a histogram object given an array of values and an attribute type.

HistogramDiscrete(Node[], AttributeDiscrete) - Constructor for class netkit.util.HistogramDiscrete

This constructor is a convenience for accepting all node values without any minimum occurance.

HistogramDiscrete(Edge[], AttributeDiscrete) - Constructor for class netkit.util.HistogramDiscrete

This constructor is a convenience for accepting all edge values without any minimum occurance.

HistogramDiscrete(Node[], AttributeDiscrete, int) - Constructor for class netkit.util.HistogramDiscrete

This constructor creates a histogram object given an array of nodes and an attribute from which to get the values.

HistogramDiscrete(Edge[], AttributeDiscrete, int) - Constructor for class netkit.util.HistogramDiscrete

This constructor creates a histogram object given an array of edges and an attribute from which to get the values.

I

idMatrix - Variable in class netkit.inference.InferenceMethod

IM_PREFIX - Static variable in class netkit.classifiers.NetworkLearning

imethods - Static variable in class netkit.classifiers.NetworkLearning

includeClassAttribute() - Method in class netkit.classifiers.relational.NetworkClassifierImp

Method to tell this object whether to include the class attribute when creating the internal instance representation for relational learning.

includeClassAttribute() - Method in class netkit.classifiers.relational.NetworkWeka

This classifier needs to include the class attribute at all times because the Weka classifier needs it.

Incremental - Interface in netkit.classifiers

IncrementalAssessment - Interface in netkit.classifiers

induceModel(Graph, DataSplit) - Method in interface netkit.classifiers.Classifier

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.ClassifierImp

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.nonrelational.ExternalPrior

Inducing this model simply means to read the estimates from the input file.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.nonrelational.LocalMetaClassifier

This induces each of the local classifiers individually.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.nonrelational.LocalWeka

Induce the weka classifier by creating a training Instances object according to the schema of the nodes to be classified.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.nonrelational.MetaMultiplicative

Induce the model.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.nonrelational.UniformPrior

Makes a uniform prediction array---all classes are equally likely

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

Induce the cdRN model by finding the 'prototypical' neighborhood for each class of nodes.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.Harmonic

Harmonic has no model per se as its learning consists of computing the harmonic function which results in the predictions.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.MetaMultiplicative

Induce the model.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.NetworkClassifierImp

This method induces a new prediction model.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.NetworkMetaClassifier

This separately induces all the non-relational and relational classifiers in addition to any setup the super-class needs to do.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.NetworkOnlyBayes

Induce the model by computing the counts for Prob(classIdx | neighborClassIdx)

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.NetworkWeka

Induce the weka classifier by creating a training Instances object according to the schema of the nodes to be classified.

induceModel(Graph, DataSplit) - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

wvRN has no model, so this only initializes what needs to be done for laplace correction (in addition to whatever the superclass does).

InferenceMethod - Class in netkit.inference

InferenceMethod() - Constructor for class netkit.inference.InferenceMethod

InferenceMethodListener - Interface in netkit.inference

init() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

initialize(NetworkLearner, DataSplit) - Method in class netkit.classifiers.active.ComparatorLabeler

initialize(NetworkLearner, DataSplit) - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

initialize(NetworkLearner, DataSplit) - Method in class netkit.classifiers.active.ERMHybrid

initialize(NetworkLearner, DataSplit) - Method in class netkit.classifiers.active.GraphCentralityLabeling

initialize(GraphCentralityLabeling) - Method in class netkit.classifiers.active.graphfunctions.ERMRank

initialize(GraphCentralityLabeling) - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

initialize(NetworkLearner, DataSplit) - Method in class netkit.classifiers.active.GreedyTruth

initialize(NetworkLearner, DataSplit) - Method in interface netkit.classifiers.active.PickLabelStrategy

Initialize the label strategy by providing a reference to the NetworkLeaner object that calls the strategy, thereby giving it access to all information it is likely to need.

initialize(NetworkLearner, DataSplit) - Method in class netkit.classifiers.active.PickLabelStrategyImp

initialize(Graph) - Static method in class netkit.classifiers.aggregators.SharedNodeInfo

Assume that we will be doing aggregation over this particular graph until further notice

initialize(Graph, String, int, double, int) - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

initialize(Graph, String, int, double, int) - Method in interface netkit.graph.edgecreator.EdgeCreator

Initialize this creator.

initialize(Graph, String, int, double, int) - Method in class netkit.graph.edgecreator.EdgeCreatorImp

initialize(Graph, String, int, double, int) - Method in class netkit.graph.edgecreator.NormalizedNumericEdgeCreator

initializeRun(Estimate, Node[]) - Method in class netkit.classifiers.relational.Harmonic

This initializes Harmonic function for the next collective inference iteration by doing absolutely nothing.

initializeRun(Estimate, Node[]) - Method in interface netkit.classifiers.relational.NetworkClassifier

This is called prior to predicting labels for the unknown labels in the graph, in case the classifier needs to initialize itself.

initializeRun(Estimate, Node[]) - Method in class netkit.classifiers.relational.NetworkClassifierImp

This is called prior to predicting labels for the unknown labels in the graph, in case the classifier needs to initialize itself.

initializeRun(Estimate, Node[]) - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

This initializes wvRN for the next collective inference iteration by setting up the laplace correction, if needed, for the current iteration.

initialPrior - Variable in class netkit.inference.InferenceMethod

initQueue() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

inTrainingSet(Node) - Method in class netkit.classifiers.NetworkLearner

invert() - Method in class netkit.util.Matrix

isActive() - Method in class netkit.util.ModularityClusterer

isByAttribute() - Method in class netkit.graph.edgecreator.CosineDistanceEdgeCreator

isByAttribute() - Method in interface netkit.graph.edgecreator.EdgeCreator

Is this edge creator by attribute or by instance as a whole

isByAttribute() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

isByAttribute() - Method in class netkit.graph.edgecreator.EuclideanDistanceEdgeCreator

isByAttribute() - Method in class netkit.graph.edgecreator.MahalanobisDistanceEdgeCreator

isByAttributeValue() - Method in class netkit.graph.edgecreator.BaseCategoricalEdgeCreator

isByAttributeValue() - Method in interface netkit.graph.edgecreator.EdgeCreator

Is this edge creator by attribute value or by attribute as a whole

isByAttributeValue() - Method in class netkit.graph.edgecreator.EdgeCreatorImp

isByValue(String) - Method in class netkit.classifiers.aggregators.AggregatorFactory

Checks to see if the aggregator by the given name is an instance of AggregatorByValue

isEmpty() - Method in class netkit.util.UpdatablePriorityQueue

isMissing(int) - Method in class netkit.graph.Node

Return whether the value associated with the attribute field at the supplied index is missing.

isMissing(String) - Method in class netkit.graph.Node

Get whether the value associated with the named attribute field is "missing".

isSquare() - Method in class netkit.util.Matrix

isSymmetric() - Method in class netkit.util.Matrix

isUnknown(Node) - Method in class netkit.classifiers.Classification

iterate(NetworkClassifier) - Method in class netkit.inference.GibbsSampling

iterate(NetworkClassifier) - Method in class netkit.inference.InferenceMethod

iterate(Graph, int[]) - Method in interface netkit.inference.InferenceMethodListener

iterate(NetworkClassifier) - Method in class netkit.inference.IterativeClassification

iterate(NetworkClassifier) - Method in class netkit.inference.NullInference

iterate(NetworkClassifier) - Method in class netkit.inference.RelaxationLabeling

iteration - Variable in class netkit.classifiers.active.PickLabelStrategyImp

IterativeClassification - Class in netkit.inference

IterativeClassification() - Constructor for class netkit.inference.IterativeClassification

iterator() - Method in class netkit.classifiers.Classification

iterator() - Method in class netkit.classifiers.DataView

iterator() - Method in class netkit.classifiers.Estimate

iterator() - Method in class netkit.graph.Attributes

Get an Iterator over the Attribute fields; iteration is performed in the order that each Attribute was added to this container.

iterator() - Method in class netkit.util.ModularityClusterer.Cluster

iterator() - Method in class netkit.util.UpdatablePriorityQueue

Returns an iterator over the elements in this queue.

K

keyIndex - Variable in class netkit.classifiers.ClassifierImp

L

l1diff(double[], double[]) - Static method in class netkit.util.VectorMath

l1diff(int[], int[]) - Static method in class netkit.util.VectorMath

l2_length(double[]) - Static method in class netkit.util.VectorMath

l2_normalize(double[]) - Static method in class netkit.util.VectorMath

la_alphaCentrality - Variable in class netkit.util.ApproximateCentralities

la_pagerank - Variable in class netkit.util.ApproximateCentralities

la_weightedAlphaCentrality - Variable in class netkit.util.ApproximateCentralities

la_weightedPagerank - Variable in class netkit.util.ApproximateCentralities

LabelClosenessRank - Class in netkit.classifiers.active.graphfunctions

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

LabelClosenessRank() - Constructor for class netkit.classifiers.active.graphfunctions.LabelClosenessRank

labeler - Variable in class netkit.classifiers.active.graphfunctions.ScoringFunction

labels - Variable in class netkit.classifiers.active.graphfunctions.ScoringFunction

LabelWeightedClosenessRank - Class in netkit.classifiers.active.graphfunctions

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

LabelWeightedClosenessRank() - Constructor for class netkit.classifiers.active.graphfunctions.LabelWeightedClosenessRank

LaplaceCorrection - Enum in netkit.util

LC_PREFIX - Static variable in class netkit.classifiers.NetworkLearning

lclassifiers - Static variable in class netkit.classifiers.NetworkLearning

lclassifiers - Variable in class netkit.classifiers.nonrelational.LocalMetaClassifier

The list of classifiers to combine

lclassifiers - Variable in class netkit.classifiers.relational.NetworkMetaClassifier

The list of non-relational classifiers to use

learning - Static variable in class netkit.Netkit

lnFactorial(int) - Method in class netkit.classifiers.bayes.NaiveBayesMultinomial

Fast computation of ln(n!) for non-negative ints negative ints are passed on to the general gamma-function based version in weka.core.SpecialFunctions if the current n value is higher than any previous one, the cache is extended and filled to cover it the common case is reduced to a simple array lookup

LocalMetaClassifier - Class in netkit.classifiers.nonrelational

Abstract class for combining multiple classifiers.

LocalMetaClassifier() - Constructor for class netkit.classifiers.nonrelational.LocalMetaClassifier

LocalWeka - Class in netkit.classifiers.nonrelational

Weka wrapper that uses a specified weka classifier to do its predictions.

LocalWeka() - Constructor for class netkit.classifiers.nonrelational.LocalWeka

logger - Variable in class netkit.classifiers.active.PickLabelStrategyImp

logger - Variable in class netkit.classifiers.ClassifierImp

logger - Variable in class netkit.classifiers.NetworkLearner

logger - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

logger - Variable in class netkit.inference.InferenceMethod

logger - Variable in class netkit.util.ComputeProcess

logger - Static variable in class netkit.util.GraphMetrics

LogRecordFormatter - Class in netkit.util

LogRecordFormatter() - Constructor for class netkit.util.LogRecordFormatter

logTime(String) - Static method in class netkit.util.NetKitEnv

M

MahalanobisDistanceEdgeCreator - Class in netkit.graph.edgecreator

MahalanobisDistanceEdgeCreator() - Constructor for class netkit.graph.edgecreator.MahalanobisDistanceEdgeCreator

main(String[]) - Static method in class netkit.classifiers.bayes.NaiveBayesMultinomial

Main method for testing this class.

main(String[]) - Static method in class netkit.classifiers.DataSampler

main(String[]) - Static method in class netkit.classifiers.NetworkLearning

Deprecated. You should use Netkit.main to access NetworkLearning from now on

main(String[]) - Static method in class netkit.graph.Graph

main(String[]) - Static method in class netkit.graph.io.SchemaReader

A test driver for the class.

main(String[]) - Static method in class netkit.graph.io.SchemaWriter

A test driver for the class.

main(String[]) - Static method in class netkit.graph.io.SplitParser

main(String[]) - Static method in class netkit.Netkit

main(String...) - Static method in class netkit.util.ApproximateCentralities

main(String[]) - Static method in class netkit.util.Histogram

This is a main driver to test the Histogram hierarchy classes.

main(String[]) - Static method in class netkit.util.Matrix

main(String[]) - Static method in class netkit.util.ModularityClusterer

makeVector(Node, double[]) - Method in class netkit.classifiers.ClassifierImp

makeVector(Node, double[]) - Method in class netkit.classifiers.relational.NetworkClassifierImp

matcher - Variable in class netkit.graph.io.SplitParser

The Matcher object used to parse each line.

Matrix - Class in netkit.util

Simple Matrix mathematics in support for the Harmonic function.

Matrix(double[][]) - Constructor for class netkit.util.Matrix

Matrix(int, int) - Constructor for class netkit.util.Matrix

Matrix(int, int, boolean) - Constructor for class netkit.util.Matrix

Max - Class in netkit.classifiers.aggregators

The Max aggregator returns the maximum value observed for a continuous attribute in the neighborhood of a node in the graph.

Max(EdgeType, Attribute) - Constructor for class netkit.classifiers.aggregators.Max

maxDist(double[], double[]) - Static method in class netkit.util.VectorMath

maxEdges - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

Mean - Class in netkit.classifiers.aggregators

The Mean aggregator returns the mean value observed for a continuous attribute in the neighborhood of a node in the graph.

Mean(EdgeType, Attribute) - Constructor for class netkit.classifiers.aggregators.Mean

merge(double, double[], double[]) - Static method in class netkit.util.VectorMath

combine arrays 1 and 2: result = alpha*arr1 + (1-alpha)*arr2

merge(double, double[], double[], double[]) - Static method in class netkit.util.VectorMath

combine arrays 1 and 2: result = alpha*arr1 + (1-alpha)*arr2

MetaMultiplicative - Class in netkit.classifiers.nonrelational

a classifier that multiplies the predictions of one or more classifiers and returns a normalized distribution as its own estimate.

MetaMultiplicative() - Constructor for class netkit.classifiers.nonrelational.MetaMultiplicative

MetaMultiplicative - Class in netkit.classifiers.relational

a classifier that multiplies the predictions of one or more classifiers and returns a normalized distribution as its own estimate.

MetaMultiplicative() - Constructor for class netkit.classifiers.relational.MetaMultiplicative

metrics - Variable in class netkit.util.ApproximateCentralities

Min - Class in netkit.classifiers.aggregators

The Min aggregator returns the minimum value observed for a continuous attribute in the neighborhood of a node in the graph.

Min(EdgeType, Attribute) - Constructor for class netkit.classifiers.aggregators.Min

Mode - Class in netkit.classifiers.aggregators

The Mode aggregator counts the number of times each possible value of a given attribute is observed in the neighborhood of a node in the graph and returns the value that is observed the most.

Mode(EdgeType, Attribute) - Constructor for class netkit.classifiers.aggregators.Mode

ModularityClusterer - Class in netkit.util

Modularity-based clusterer, extended to work with weights, multiple edges, and directed edges.

ModularityClusterer(Graph) - Constructor for class netkit.util.ModularityClusterer

ModularityClusterer.Cluster - Class in netkit.util

multiply(Matrix) - Method in class netkit.util.Matrix

multiply(double[], double) - Static method in class netkit.util.VectorMath

Multiply array by given factor

N

NaiveBayesMultinomial - Class in netkit.classifiers.bayes

The core equation for this classifier: P[Ci|D] = (P[D|Ci] x P[Ci]) / P[D] (Bayes rule) where Ci is class i and D is a document

NaiveBayesMultinomial() - Constructor for class netkit.classifiers.bayes.NaiveBayesMultinomial

name - Variable in class netkit.classifiers.aggregators.AggregatorImp

name() - Method in class netkit.util.ComputeProcess

nat - Variable in class netkit.graph.edgecreator.BaseNumericEdgeCreator

netkit - package netkit

Netkit - Class in netkit

Netkit() - Constructor for class netkit.Netkit

netkit.classifiers - package netkit.classifiers

netkit.classifiers.active - package netkit.classifiers.active

netkit.classifiers.active.graphfunctions - package netkit.classifiers.active.graphfunctions

netkit.classifiers.aggregators - package netkit.classifiers.aggregators

netkit.classifiers.bayes - package netkit.classifiers.bayes

netkit.classifiers.io - package netkit.classifiers.io

netkit.classifiers.nonrelational - package netkit.classifiers.nonrelational

netkit.classifiers.relational - package netkit.classifiers.relational

netkit.graph - package netkit.graph

netkit.graph.edgecreator - package netkit.graph.edgecreator

netkit.graph.io - package netkit.graph.io

netkit.inference - package netkit.inference

netkit.util - package netkit.util

NetKitEnv - Class in netkit.util

NetKitEnv() - Constructor for class netkit.util.NetKitEnv

NetkitGraph - Class in netkit.graph.io

NetkitGraph() - Constructor for class netkit.graph.io.NetkitGraph

NetworkClassifier - Interface in netkit.classifiers.relational

Interface for a relational classifier in addition to those of a nonrelational classifier.

NetworkClassifierImp - Class in netkit.classifiers.relational

Core implementation of the NetworkClassifier (and Classifier) interface.

NetworkClassifierImp() - Constructor for class netkit.classifiers.relational.NetworkClassifierImp

NetworkClassifierImp.Aggregation - Enum in netkit.classifiers.relational

The possible ways the relational classifier can handle aggregation.

NetworkLearner - Class in netkit.classifiers

NetworkLearner(Classifier, NetworkClassifier, InferenceMethod, boolean) - Constructor for class netkit.classifiers.NetworkLearner

NetworkLearning - Class in netkit.classifiers

NetworkLearning(String[]) - Constructor for class netkit.classifiers.NetworkLearning

NetworkMetaClassifier - Class in netkit.classifiers.relational

Abstract class for combining multiple relational and non-relational classifiers.

NetworkMetaClassifier() - Constructor for class netkit.classifiers.relational.NetworkMetaClassifier

NetworkOnlyBayes - Class in netkit.classifiers.relational

Network-only Bayes Classifier induces a naive Bayes model based on labels of neighbors of a node and uses a Markov random field formulation when one or more neighbors have estimated labels.

NetworkOnlyBayes() - Constructor for class netkit.classifiers.relational.NetworkOnlyBayes

NetworkWeka - Class in netkit.classifiers.relational

Weka wrapper that uses a specified weka classifier to do its predictions.

NetworkWeka() - Constructor for class netkit.classifiers.relational.NetworkWeka

newline - Static variable in class netkit.util.NetKitEnv

next() - Method in class netkit.util.ArrayIterator

node - Variable in class netkit.classifiers.active.PickLabelStrategy.LabelNode

Node - Class in netkit.graph

This class represents a node in the Graph object.

Node(String, Attributes, int) - Constructor for class netkit.graph.Node

The constructor must be provided with a name, an Attributes container and an index.

NodeFilter - Interface in netkit.graph

A filter for Nodes.

NodeReader - Class in netkit.graph.io

This class reads Node instance data from a Reader object.

NodeReader() - Constructor for class netkit.graph.io.NodeReader

nodes - Variable in class netkit.graph.edgecreator.BaseNumericEdgeCreator

nodeType - Variable in class netkit.classifiers.ClassifierImp

nodeType - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

nodeType - Variable in class netkit.util.GraphMetrics

NodeWriter - Class in netkit.graph.io

This class writes Node instance data to a Writer object.

NodeWriter() - Constructor for class netkit.graph.io.NodeWriter

normalize(Node) - Method in class netkit.classifiers.Estimate

normalize(double[]) - Static method in class netkit.util.VectorMath

NormalizedNumericEdgeCreator - Class in netkit.graph.edgecreator

NormalizedNumericEdgeCreator() - Constructor for class netkit.graph.edgecreator.NormalizedNumericEdgeCreator

notifyListeners(Node, double[]) - Method in interface netkit.classifiers.Classifier

notifyListeners(Node, int) - Method in interface netkit.classifiers.Classifier

notifyListeners(Node, double[]) - Method in class netkit.classifiers.ClassifierImp

notifyListeners(Node, int) - Method in class netkit.classifiers.ClassifierImp

notifyListeners(Estimate, int[]) - Method in class netkit.inference.InferenceMethod

notifyListeners(Classification, int[]) - Method in class netkit.inference.InferenceMethod

notifyListeners(Graph, int[]) - Method in class netkit.inference.InferenceMethod

NullInference - Class in netkit.inference

NullInference() - Constructor for class netkit.inference.NullInference

NullPrior - Class in netkit.classifiers.nonrelational

Predict nothing.

NullPrior() - Constructor for class netkit.classifiers.nonrelational.NullPrior

numEdges() - Method in class netkit.graph.Graph

Gets the total number of edges in this graph.

numEdges(String) - Method in class netkit.graph.Graph

Gets the number of Edges in this graph for the supplied EdgeType name.

numEdges() - Method in class netkit.graph.Node

Gets the total number of edges for this node.

numEdges(String) - Method in class netkit.graph.Node

Gets the number of Edges to neighboring Nodes with the supplied EdgeType name.

numEdges - Variable in class netkit.util.GraphMetrics

numIterations - Variable in class netkit.inference.InferenceMethod

numMissingValues() - Method in class netkit.classifiers.DataSampler

numNodes() - Method in class netkit.graph.Graph

Gets the total number of nodes in this graph.

numNodes(String) - Method in class netkit.graph.Graph

Gets the number of nodes in the graph for the supplied node type.

numNodes - Variable in class netkit.util.GraphMetrics

P

pagerank - Variable in class netkit.util.ApproximateCentralities

pairedTTest(double[], double[]) - Static method in class netkit.util.StatUtil

PajekGraph - Class in netkit.graph.io

PajekGraph() - Constructor for class netkit.graph.io.PajekGraph

parseAndInsert(String) - Method in class netkit.graph.Attribute

Parses the supplied string token for insertion into this attribute and converts the token into a double value.

parseAndInsert(String) - Method in class netkit.graph.AttributeContinuous

Parses the supplied string token for insertion into this attribute and converts the token into a double value; a "?" token results in NaN.

parseAndInsert(String) - Method in class netkit.graph.AttributeDiscrete

Parses the supplied string token for insertion into this attribute and converts the token into a double value; a "?" token results in NaN.

parseAndInsert(String) - Method in class netkit.graph.AttributeExpandableCategorical

Parses the supplied string token for insertion into this attribute and converts the token into a double value; if the token is "?", that results in NaN.

parseAndInsert(String) - Method in class netkit.graph.AttributeFixedCategorical

Parses the supplied string token for insertion into this attribute and converts the token into a double value; if the token is "?", that results in NaN.

parseAndInsert(String) - Method in class netkit.graph.AttributeIgnore

Parses the supplied string token for insertion into this attribute and converts the token into a double value; a "?" token results in NaN.

parseAndInsert(String) - Method in class netkit.graph.AttributeKey

Parses the supplied string token for insertion into this attribute and converts the token into a double value;

parseLine(CharSequence) - Method in class netkit.graph.io.SplitParser

Parses a line of text according to the regex defined for this parser and splits it into an array of String.

peek(DataSplit, Estimate, int) - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

peek(DataSplit, Estimate, int) - Method in class netkit.classifiers.active.GraphCentralityLabeling

peek(DataSplit, Estimate, int) - Method in class netkit.classifiers.active.GreedyTruth

peek(DataSplit, Estimate, int) - Method in interface netkit.classifiers.active.PickLabelStrategy

Get the list of nodes to get labels for...

peek(DataSplit, Estimate, int) - Method in class netkit.classifiers.active.PickLabelStrategyImp

peek(DataSplit, Estimate, int) - Method in class netkit.classifiers.active.UncertaintyLabeling

peek() - Method in class netkit.util.UpdatablePriorityQueue

percentDone() - Method in class netkit.util.ModularityClusterer

PickLabelStrategy - Interface in netkit.classifiers.active

PickLabelStrategy.LabelNode - Class in netkit.classifiers.active

PickLabelStrategy.LabelNode(Node, double) - Constructor for class netkit.classifiers.active.PickLabelStrategy.LabelNode

PickLabelStrategyImp - Class in netkit.classifiers.active

PickLabelStrategyImp() - Constructor for class netkit.classifiers.active.PickLabelStrategyImp

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.ComparatorLabeler

Maxpicks are ignored.

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.EmpiricalRiskMinimization

Get the next nodes to label based on the empirical risk minimization principle.

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.EmpiricalRiskMinimizationHarmonic

Get the next nodes to label based on the empirical risk minimization principle.

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.ERMHybrid

Maxpicks are ignored.

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.GraphCentralityLabeling

Picks the next nodes as the ones with the highest closeness centrality (normalized by cluster size) in a cluster that has no known labels.

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.GreedyTruth

Get the next nodes to label based on the empirical risk minimization principle.

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.PickLabelStrategyImp

Get the list of nodes to get labels for.

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.RandomLabeling

pickNodes(Estimate, int) - Method in class netkit.classifiers.active.UncertaintyLabeling

pickRandom - Static variable in class netkit.util.VectorMath

poll() - Method in class netkit.util.UpdatablePriorityQueue

print(Node, Estimate) - Method in class netkit.classifiers.io.PrintEstimateWriter

Print an estimate of the given node using the given output format and the given current estimates.

print(Node, Estimate, Classification) - Method in class netkit.classifiers.io.PrintEstimateWriter

Print an estimate of the given node using the given output format and the given current estimates and true labels.

print(PrintWriter) - Method in class netkit.util.Matrix

printDegreeDistribution(Graph) - Method in class netkit.GraphStat

PrintEstimateWriter - Class in netkit.classifiers.io

This class prints label estimates in a user-defined output format.

PrintEstimateWriter(PrintWriter, String) - Constructor for class netkit.classifiers.io.PrintEstimateWriter

PrintEstimateWriter(PrintWriter) - Constructor for class netkit.classifiers.io.PrintEstimateWriter

PrintEstimateWriter(PrintStream, String) - Constructor for class netkit.classifiers.io.PrintEstimateWriter

PrintEstimateWriter(PrintStream) - Constructor for class netkit.classifiers.io.PrintEstimateWriter

printGlobalInfo(Graph) - Method in class netkit.GraphStat

println(Node, Estimate) - Method in class netkit.classifiers.io.PrintEstimateWriter

Print an estimate line of the given node using the given output format and the given current estimates.

println(Node, Estimate, Classification) - Method in class netkit.classifiers.io.PrintEstimateWriter

Print an estimate line of the given node using the given output format and the given current estimates and true labels.

printLoggers() - Static method in class netkit.util.NetKitEnv

printMatrix(PrintWriter) - Method in class netkit.util.ConfusionMatrix

printNetKitEdges(Graph, PrintWriter, String) - Static method in class netkit.graph.io.NetkitGraph

printNetKitNodes(Graph, PrintWriter, String) - Static method in class netkit.graph.io.NetkitGraph

printNetKitNodes(Graph, PrintWriter, String, boolean, boolean) - Static method in class netkit.graph.io.NetkitGraph

printNodeStatistics(Graph) - Method in class netkit.GraphStat

printStat(String) - Method in class netkit.classifiers.active.GraphCentralityLabeling

prior - Variable in class netkit.classifiers.relational.NetworkClassifierImp

This keeps track of the priors for the unknown nodes.

ProbRelationalNeighbor - Class in netkit.classifiers.relational

This is a probablistic version of wbRN and it estimates nodes by using a Bayesian combination of the neighbors edges.

ProbRelationalNeighbor() - Constructor for class netkit.classifiers.relational.ProbRelationalNeighbor

progress - Variable in class netkit.util.ComputeProcess

progress() - Method in class netkit.util.ComputeProcess

pruneLess(Graph, EdgeType, double) - Static method in class netkit.EdgeTransformer

pruneMinK(Graph, EdgeType, int, boolean) - Static method in class netkit.EdgeTransformer

pruneMore(Graph, EdgeType, double) - Static method in class netkit.EdgeTransformer

pruneTopK(Graph, EdgeType, int, boolean) - Static method in class netkit.EdgeTransformer

R

randomize(T[]) - Static method in class netkit.util.VectorMath

randomize(T[], int) - Static method in class netkit.util.VectorMath

randomize(T[], T[]) - Static method in class netkit.util.VectorMath

randomize(T[], T[], int) - Static method in class netkit.util.VectorMath

randomize(int[]) - Static method in class netkit.util.VectorMath

randomize(int[], int) - Static method in class netkit.util.VectorMath

randomize(int[], int[]) - Static method in class netkit.util.VectorMath

randomize(int[], int[], int) - Static method in class netkit.util.VectorMath

randomize(double[]) - Static method in class netkit.util.VectorMath

randomize(double[], int) - Static method in class netkit.util.VectorMath

randomize(double[], double[]) - Static method in class netkit.util.VectorMath

randomize(double[], double[], int) - Static method in class netkit.util.VectorMath

RandomLabeling - Class in netkit.classifiers.active

RandomLabeling() - Constructor for class netkit.classifiers.active.RandomLabeling

Ratio - Class in netkit.classifiers.aggregators

The Ratio aggregator counts the ratio of times a specific value of a given attribute is observed in the neighborhood of a node in the graph.

Ratio(EdgeType, Attribute, double) - Constructor for class netkit.classifiers.aggregators.Ratio

RC_PREFIX - Static variable in class netkit.classifiers.NetworkLearning

rclassifiers - Static variable in class netkit.classifiers.NetworkLearning

rclassifiers - Variable in class netkit.classifiers.relational.NetworkMetaClassifier

The list of relational classifiers to use

ReadClassification - Interface in netkit.classifiers.io

This interface defines the methods needed to read a set of true classifications from a file.

readClassification(Graph, String, AttributeCategorical, File) - Method in interface netkit.classifiers.io.ReadClassification

Read from a given file a estimate of classifications for nodes in the given graph.

readClassification(Graph, Classification, File) - Method in interface netkit.classifiers.io.ReadClassification

Read from a given file a estimate of classifications for nodes in the given graph.

readClassification(Graph, String, AttributeCategorical, File) - Method in class netkit.classifiers.io.ReadClassificationGeneric

Creates a new Classification object based on the graph, nodeType and attribute and then calls the generic readClassification method.

readClassification(Graph, Classification, File) - Method in class netkit.classifiers.io.ReadClassificationGeneric

Reads in a set of classifications from the given file, assuming that each line is of the form 'nodeID,class'.

ReadClassificationGeneric - Class in netkit.classifiers.io

Reads in true labels of entities in a graph from a file where the format of each line is: nodeID,class Lines starting with '#' are ignored

ReadClassificationGeneric() - Constructor for class netkit.classifiers.io.ReadClassificationGeneric

readEdges(Reader, EdgeType) - Method in class netkit.EdgeTransformer

readEdges(Reader, Graph, EdgeType) - Static method in class netkit.graph.io.EdgeReaderGDA

Reads Edges from the supplied Reader and creates the corresponding Edges in the Graph; Edges are validated by the supplied EdgeType which must have identical source and destination Node types, and the Nodes these Edges refer to must already exist in the Graph.

readEdges(Reader, Graph, EdgeType, EdgeType) - Static method in class netkit.graph.io.EdgeReaderRN

Reads Edges from the supplied Reader and creates the corresponding Edges in the Graph; Edges are validated by the the supplied EdgeTypes and the Nodes these Edges refer to must already exist in the Graph.

ReadEstimate - Interface in netkit.classifiers.io

This interface defines the methods needed to read a set of predictions from a file.

readEstimate(Graph, String, AttributeCategorical, File) - Method in interface netkit.classifiers.io.ReadEstimate

Read from a given file an estimate for nodes in the given graph.

readEstimate(Graph, Estimate, File) - Method in interface netkit.classifiers.io.ReadEstimate

Read from a given file estimates for nodes in the given graph.

readEstimate(Graph, String, AttributeCategorical, File) - Method in class netkit.classifiers.io.ReadEstimateRainbow

Create a new Estimate object and call the more general readEstimate method.

readEstimate(Graph, Estimate, File) - Method in class netkit.classifiers.io.ReadEstimateRainbow

Reads in a set of estimates from the given file, assuming that each line is of the form: nodeID trueclass class:score ...

ReadEstimateRainbow - Class in netkit.classifiers.io

Reads in estimates of entities in a graph from a file where the format of each line is: nodeID trueclass class:score ...

ReadEstimateRainbow() - Constructor for class netkit.classifiers.io.ReadEstimateRainbow

readGDASchema(File, File) - Static method in class netkit.graph.io.SchemaReader

Overloaded entry point for SchemaReader.readGDASchema(Reader,Reader)

readGDASchema(Reader, Reader) - Static method in class netkit.graph.io.SchemaReader

Reads the Node and Edge information from GDA formatted input, constructs the data structures and instantiates all of the instance data.

readGraph(File) - Static method in class netkit.graph.io.NetkitGraph

readGraph(File) - Static method in class netkit.graph.io.PajekGraph

Overloaded entry point for PajekGraph.readGraph(Reader)

readGraph(Reader) - Static method in class netkit.graph.io.PajekGraph

Reads the Graph information from Pajek formatted input, constructs the data structures and instantiates all of the instance data.

readNodes(Graph, String, Reader, boolean) - Static method in class netkit.graph.io.NodeReader

This static method does the work of reading input data for the class.

ReadPrior - Class in netkit.classifiers.io

This class reads in class priors from a file such that a user can specify the priors rather than have the classifier use the priors that are estimated from training examples.

ReadPrior() - Constructor for class netkit.classifiers.io.ReadPrior

readPrior(File, AttributeCategorical) - Static method in class netkit.classifiers.io.ReadPrior

Reads in a file using the file format mentioned in the header.

readPrior(BufferedReader, AttributeCategorical) - Static method in class netkit.classifiers.io.ReadPrior

Reads in a file using the file format mentioned in the header.

readSchema(File) - Static method in class netkit.graph.io.SchemaReader

Overloaded entry point for SchemaReader.readSchema(Reader,String)

readSchema(Reader, String) - Static method in class netkit.graph.io.SchemaReader

Reads the Graph information from a schema file, constructs the data structures and instantiates all of the instance data.

RelaxationLabeling - Class in netkit.inference

RelaxationLabeling() - Constructor for class netkit.inference.RelaxationLabeling

remove(int) - Method in class netkit.graph.Attributes

Removes the Attribute at the specified index.

remove(String) - Method in class netkit.graph.Attributes

Removes the Attribute specified by the supplied field name.

remove() - Method in class netkit.util.ArrayIterator

remove(UpdatablePriorityQueue<E>.QueueElement) - Method in class netkit.util.UpdatablePriorityQueue

Removes a single instance of the specified element from this queue, if it is present.

remove(E) - Method in class netkit.util.UpdatablePriorityQueue

Removes a single instance of the specified element from this queue, if it is present.

removeAttribute(String, int) - Method in class netkit.graph.Graph

Remove an Attribute at the supplied index from the Attributes container represented by the supplied nodeType name.

removeAttributes(String, boolean) - Method in class netkit.graph.Graph

Remove the supplied Attributes container (AKA nodeType) from this Graph.

removeEdge(String, Node, Node) - Method in class netkit.graph.Graph

Removes the Edge connecting the supplied source Node and destination Node through the supplied EdgeType.

removeEdge(String, Node) - Method in class netkit.graph.Node

Removes the Edge to the supplied destination Node via the supplied EdgeType name.

removeEdges(String) - Method in class netkit.graph.Graph

Removes all Edges from this Graph sharing the supplied EdgeType.

removeEdgeType(String, boolean) - Method in class netkit.graph.Graph

Remove the supplied EdgeType from this Graph.

removeListener(ClassifierListener) - Method in interface netkit.classifiers.Classifier

removeListener(ClassifierListener) - Method in class netkit.classifiers.ClassifierImp

removeListener(InferenceMethodListener) - Method in class netkit.inference.InferenceMethod

removeNewEdges() - Method in class netkit.util.GraphView

removeNodes(String, boolean) - Method in class netkit.graph.Graph

Remove all Nodes in this Graph whose Attributes container (AKA nodeType) matches the supplied nodeType.

removeValue(int) - Method in class netkit.graph.Node

Removes the value from the values array at the specified index and shrinks the values array accordingly.

reset() - Method in interface netkit.classifiers.Classifier

reset() - Method in class netkit.classifiers.ClassifierImp

reset() - Method in class netkit.classifiers.relational.NetworkOnlyBayes

Resets internal variables.

reset(Iterator<Node>) - Method in class netkit.inference.GibbsSampling

reset(Iterator<Node>) - Method in class netkit.inference.InferenceMethod

reset(Iterator<Node>) - Method in class netkit.inference.IterativeClassification

reset(Iterator<Node>) - Method in class netkit.inference.NullInference

reset(Iterator<Node>) - Method in class netkit.inference.RelaxationLabeling

reset() - Method in class netkit.util.GraphView

resetOptions() - Method in class netkit.EdgeTransformer

resetTime() - Static method in class netkit.util.NetKitEnv

resetTruth() - Method in class netkit.classifiers.DataView

resetWeights() - Method in class netkit.util.GraphView

residual - Variable in class netkit.util.ApproximateCentralities.ApproximateCentrality

ReverseScoringFunction - Class in netkit.classifiers.active.graphfunctions

ReverseScoringFunction() - Constructor for class netkit.classifiers.active.graphfunctions.ReverseScoringFunction

reweight(Graph, EdgeType, double) - Static method in class netkit.EdgeTransformer

reweight(Graph, Edge[], double) - Static method in class netkit.EdgeTransformer

right - Variable in class netkit.classifiers.ClassifierImp

ROC - Class in netkit.util

ROC(Estimate, Classification, int) - Constructor for class netkit.util.ROC

run() - Method in class netkit.classifiers.NetworkLearning

run(String[]) - Static method in class netkit.classifiers.NetworkLearning

run() - Method in class netkit.EdgeTransformer

run(String[]) - Static method in class netkit.EdgeTransformer

run(Graph) - Method in class netkit.GraphStat

run(String[]) - Static method in class netkit.GraphStat

run() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

run() - Method in class netkit.util.ComputeProcess

This method is the main computation method.

runActiveLearner(PickLabelStrategy, DataSplit) - Method in class netkit.classifiers.NetworkLearner

See fully parameterized method for details.

runActiveLearner(PickLabelStrategy, DataSplit, int, int, boolean, int) - Method in class netkit.classifiers.NetworkLearner

Run active learning using the given parameters.

runInference(DataSplit) - Method in class netkit.classifiers.NetworkLearner

runInference(DataSplit, boolean, boolean, int) - Method in class netkit.classifiers.NetworkLearner

runInference(DataSplit) - Method in class netkit.classifiers.NetworkLearning

runInference() - Method in class netkit.classifiers.NetworkLearning

runLeaveOneOut(DataSplit) - Method in class netkit.classifiers.NetworkLearner

runLeaveOneOut(DataSplit, boolean, int) - Method in class netkit.classifiers.NetworkLearner

S

sample(Node[]) - Method in class netkit.classifiers.DataSampler

Fill the array with sampled data

sample(int) - Method in class netkit.classifiers.DataSampler

Sample the given number of nodes and return a new array filled with the samples.

sample(int...) - Method in class netkit.classifiers.DataSampler

Sample sets of the given size from the underlying distribution of nodes and return them in a a list of lists.

sample(Node[]...) - Method in class netkit.classifiers.DataSampler

Fill the given list of arrays with sample nodes, ensuring that there is no overlap between nodes sampled in each of the sub-arrays (unless you are sampling with replacement).

sample(double) - Method in class netkit.classifiers.DataView

sample(int) - Method in class netkit.classifiers.DataView

sampleEstimateIdx(Node) - Method in class netkit.classifiers.Estimate

sampleIdx(double[]) - Static method in class netkit.util.VectorMath

sampleUnknown() - Method in class netkit.classifiers.DataSampler

save(File) - Method in class netkit.util.ROC

save(PrintWriter) - Method in class netkit.util.ROC

saveClusters(Graph) - Method in class netkit.GraphStat

saveComponents(Graph) - Method in class netkit.GraphStat

saveGraph(Graph, PrintWriter) - Static method in class netkit.graph.io.DotGraph

saveGraph(Graph, String) - Static method in class netkit.graph.io.DotGraph

saveGraph(Graph, String, boolean, boolean) - Static method in class netkit.graph.io.NetkitGraph

saveGraph(Graph, String) - Static method in class netkit.graph.io.NetkitGraph

saveGraph(Graph, PrintWriter, Classification, Estimate, String) - Static method in class netkit.graph.io.PajekGraph

saveGraph(Graph, PrintWriter) - Static method in class netkit.graph.io.PajekGraph

saveGraph(Graph, String) - Static method in class netkit.graph.io.PajekGraph

saveGraph(Graph, String, Classification, Estimate, String) - Static method in class netkit.graph.io.PajekGraph

Save the given graph as a pajek graph, to the given file, using the classification and estimate and label.

saveGraph(Graph) - Method in class netkit.GraphStat

saveIterationPredictions(String, PrintEstimateWriter, boolean, Node[], String) - Method in class netkit.classifiers.NetworkLearner

saveIterationsInPajek(String) - Method in class netkit.classifiers.NetworkLearner

saveNetKitEdges(Graph, String, String) - Static method in class netkit.graph.io.NetkitGraph

saveNetKitNodes(Graph, String, String) - Static method in class netkit.graph.io.NetkitGraph

saveNetKitNodes(Graph, String, String, boolean, boolean) - Static method in class netkit.graph.io.NetkitGraph

savePredictions(String, PrintEstimateWriter, boolean, Node[], String) - Method in class netkit.inference.InferenceMethod

savePredictionsInPajek(String) - Method in class netkit.inference.InferenceMethod

SchemaReader - Class in netkit.graph.io

This class reads schema type information for a Graph and builds the data structures to describe completely a network of Nodes and Edges, all of their type information and the instance data.

SchemaReader() - Constructor for class netkit.graph.io.SchemaReader

SchemaWriter - Class in netkit.graph.io

This class outputs schema information for a Graph.

SchemaWriter() - Constructor for class netkit.graph.io.SchemaWriter

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.Betweenness

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.Closeness

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.ClusterCloseness

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.ClusterSizeRank

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.ClusterWeightedCloseness

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.ERMRank

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.LabelClosenessRank

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.LabelWeightedClosenessRank

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.WeightedBetweenness

score(ModularityClusterer.Cluster, Node) - Method in class netkit.classifiers.active.graphfunctions.WeightedCloseness

score - Variable in class netkit.classifiers.active.PickLabelStrategy.LabelNode

score - Variable in class netkit.graph.edgecreator.EdgeCreatorImp.NbrEntry

ScoringFunction - Class in netkit.classifiers.active.graphfunctions

ScoringFunction() - Constructor for class netkit.classifiers.active.graphfunctions.ScoringFunction

set(Node, int) - Method in class netkit.classifiers.Classification

set(Node, double) - Method in class netkit.classifiers.Classification

set(String, String) - Method in class netkit.util.Configuration

set(String, double) - Method in class netkit.util.Configuration

set(String, int) - Method in class netkit.util.Configuration

set(String, long) - Method in class netkit.util.Configuration

set(String, boolean) - Method in class netkit.util.Configuration

setAlphaCentralityAlpha(double) - Method in class netkit.util.GraphMetrics

set the alpha used when computing approximate alpha centrality

setAlphaCentralityDelta(double) - Method in class netkit.util.GraphMetrics

set the delta used when computing approximate alpha centrality

setAppendStatistics(boolean) - Method in class netkit.GraphStat

setAttribute(AttributeCategorical) - Method in class netkit.classifiers.NetworkLearning

setBeta(double) - Method in class netkit.inference.RelaxationLabeling

setBeta0(double) - Method in class netkit.inference.RelaxationLabeling

setCalcAssort(boolean) - Method in class netkit.GraphStat

setClassification(Classification) - Method in class netkit.classifiers.DataView

setDataView(DataView) - Method in class netkit.classifiers.NetworkLearning

setDecay(double) - Method in class netkit.inference.RelaxationLabeling

setDegree() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

setDegreeOutput(String) - Method in class netkit.GraphStat

setDoAlphaCentralities(boolean) - Method in class netkit.GraphStat

setDoCentralities(boolean) - Method in class netkit.GraphStat

setDoClustering(boolean) - Method in class netkit.GraphStat

setDoCoefficients(boolean) - Method in class netkit.GraphStat

setDoDegree(boolean) - Method in class netkit.GraphStat

setDoPagerank(boolean) - Method in class netkit.GraphStat

setGlobalOutput(String) - Method in class netkit.GraphStat

setGraph(Graph) - Method in class netkit.classifiers.NetworkLearning

setInDegree() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

setInitialPrior(Estimate) - Method in class netkit.inference.InferenceMethod

setInput(Reader) - Method in class netkit.EdgeTransformer

setInput(String) - Method in class netkit.EdgeTransformer

setKnown(Classification) - Method in class netkit.classifiers.NetworkLearning

setLearner(NetworkLearner) - Method in class netkit.classifiers.NetworkLearning

setLogfile(String) - Static method in class netkit.util.NetKitEnv

setMinK(int) - Method in class netkit.EdgeTransformer

setNodeOutput(String) - Method in class netkit.GraphStat

setNodes() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

setNodeType(String) - Method in class netkit.classifiers.NetworkLearning

setNofityListeners(boolean) - Method in interface netkit.classifiers.Classifier

setNofityListeners(boolean) - Method in class netkit.classifiers.ClassifierImp

setNofityListeners(boolean) - Method in class netkit.inference.InferenceMethod

setNumIterations(int) - Method in class netkit.inference.InferenceMethod

setOuputFormat(String) - Method in class netkit.classifiers.NetworkLearning

setOutput(OutputStream) - Method in class netkit.classifiers.io.PrintEstimateWriter

Reset the output to the given outputstream.

setOutput(PrintWriter) - Method in class netkit.classifiers.io.PrintEstimateWriter

Reset the output to the given printwriter.

setOutput(PrintWriter) - Method in class netkit.EdgeTransformer

setOutput(String) - Method in class netkit.EdgeTransformer

setOutput(String) - Method in class netkit.GraphStat

setOutputFormat(String) - Method in class netkit.classifiers.io.PrintEstimateWriter

Reset the output format to the given format string.

setPagerankAlpha(double) - Method in class netkit.util.GraphMetrics

set the alpha used when computing approximate pagerank centrality

setPagerankDelta(double) - Method in class netkit.util.GraphMetrics

set the delta used when computing approximate pagerank centrality

setPajekColorStr(String) - Method in class netkit.GraphStat

setPajekLabel(String) - Method in class netkit.GraphStat

setParent(Configuration) - Method in class netkit.util.Configuration

setPrior(double[]) - Method in class netkit.classifiers.DataView

setPrior(double[]) - Method in class netkit.classifiers.NetworkLearning

setPruneLess(double) - Method in class netkit.EdgeTransformer

setPruneMore(double) - Method in class netkit.EdgeTransformer

setPruneSingletons(boolean) - Method in class netkit.GraphStat

setRandomSeed(long) - Method in class netkit.classifiers.NetworkLearning

setReverse(boolean) - Method in class netkit.EdgeTransformer

setReweight(double) - Method in class netkit.EdgeTransformer

setSaveAttributes(boolean) - Method in class netkit.GraphStat

setSaveClusterStem(String) - Method in class netkit.GraphStat

setSaveComponentStem(String) - Method in class netkit.GraphStat

setSaveDot(boolean) - Method in class netkit.GraphStat

setSaveGraphStem(String) - Method in class netkit.GraphStat

setSaveNetkit(boolean) - Method in class netkit.GraphStat

setSavePajek(boolean) - Method in class netkit.GraphStat

setSeed(long) - Static method in class netkit.util.VectorMath

setShowIterationAccuracies(boolean) - Method in class netkit.inference.InferenceMethod

setSplits(DataSplit[]) - Method in class netkit.classifiers.NetworkLearning

setStdOut(PrintWriter) - Static method in class netkit.util.NetKitEnv

setTest(Classification) - Method in class netkit.classifiers.NetworkLearning

setTopK(int) - Method in class netkit.EdgeTransformer

setTruth(Classification) - Method in class netkit.classifiers.DataView

setTruth(Classification) - Method in class netkit.classifiers.NetworkLearning

setTruth(Classification) - Method in class netkit.inference.InferenceMethod

setUnknown(Node) - Method in class netkit.classifiers.Classification

setupExperiment() - Method in class netkit.classifiers.NetworkLearning

setValue(int, double) - Method in class netkit.graph.Node

Sets the value associated with the attribute field at the supplied index.

setValue(String, double) - Method in class netkit.graph.Node

Sets the value associated with the named attribute field.

setValues(double[]) - Method in class netkit.graph.Node

Sets all of the values for this node.

setWeight(double) - Method in class netkit.graph.Edge

Sets the weight field of this Edge.

SharedNodeInfo - Class in netkit.classifiers.aggregators

The SharedNodeInfo class is used to cache aggregation statistics for a given node such that multiple aggregators can use the same statistics without having to calculate them more than once.

showClassValue(Node) - Method in class netkit.classifiers.DataView

showNeighbors(Node, int) - Method in class netkit.classifiers.DataView

size() - Method in class netkit.classifiers.Classification

size() - Method in class netkit.classifiers.DataSampler

size() - Method in class netkit.classifiers.DataView

size() - Method in class netkit.classifiers.Estimate

size() - Method in class netkit.graph.AttributeCategorical

Gets the size of the categorical token list.

size() - Method in class netkit.graph.TokenSet

Gets the size of the categorical token list.

size() - Method in class netkit.util.UpdatablePriorityQueue

solve() - Method in class netkit.util.Matrix

source - Variable in class netkit.graph.edgecreator.EdgeCreatorImp.NbrEntry

split - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

SplitParser - Class in netkit.graph.io

This class enables parsing lines of text using regular expression patterns that must match an entire line.

SplitParser(int, String, String, String) - Constructor for class netkit.graph.io.SplitParser

The protected constructor which creates the field holder array and assembles the regular expression for matching lines.

start() - Method in class netkit.util.ComputeProcess

startClustering() - Method in class netkit.util.ModularityClusterer

StatUtil - Class in netkit.util

StatUtil() - Constructor for class netkit.util.StatUtil

stop() - Method in class netkit.util.ComputeProcess

stop(boolean) - Method in class netkit.util.ComputeProcess

stop() - Method in class netkit.util.ModularityClusterer

stopCalcCentralityStat() - Method in class netkit.util.GraphMetrics

stopCalcClusterStat() - Method in class netkit.util.GraphMetrics

stopCalcComponentStat() - Method in class netkit.util.GraphMetrics

stressTest(int, int, int) - Static method in class netkit.graph.io.SchemaReader

This method conducts a stress test by creating a set of random nodes and edges and performs busy-work accessing the node and edge information.

subGraph(Collection<Node>) - Method in class netkit.graph.Graph

Create a sub-graph consisting only of the given nodes and the edges between those nodes.

submatrix(int, int, int, int) - Method in class netkit.util.Matrix

subtract(Matrix) - Method in class netkit.util.Matrix

subtract(double[], double[]) - Static method in class netkit.util.VectorMath

Subtract array 2 from array 1

sum(double[]) - Static method in class netkit.util.VectorMath

sum(int[]) - Static method in class netkit.util.VectorMath

systemOut - Static variable in class netkit.util.NetKitEnv

T

testGetPaths(int) - Static method in class netkit.graph.Graph

textgraph - Static variable in class netkit.Netkit

tmpPredict - Variable in class netkit.inference.InferenceMethod

tmpVector - Variable in class netkit.classifiers.ClassifierImp

toArray() - Method in class netkit.util.UpdatablePriorityQueue

Returns an array containing all of the elements in this queue.

toArray(T[]) - Method in class netkit.util.UpdatablePriorityQueue

Returns an array containing all of the elements in this queue; the runtime type of the returned array is that of the specified array.

tokenList - Variable in class netkit.graph.TokenSet

tokenMap - Variable in class netkit.graph.TokenSet

tokenSet - Variable in class netkit.graph.AttributeCategorical

TokenSet - Class in netkit.graph

This abstract class is the parent of the token set hierarchy.

TokenSet() - Constructor for class netkit.graph.TokenSet

toString() - Method in class netkit.classifiers.active.graphfunctions.Betweenness

toString() - Method in class netkit.classifiers.active.graphfunctions.Closeness

toString() - Method in class netkit.classifiers.active.graphfunctions.ClusterCloseness

toString() - Method in class netkit.classifiers.active.graphfunctions.ClusterSizeRank

toString() - Method in class netkit.classifiers.active.graphfunctions.ClusterWeightedCloseness

toString() - Method in class netkit.classifiers.active.graphfunctions.ERMRank

toString() - Method in class netkit.classifiers.active.graphfunctions.LabelClosenessRank

toString() - Method in class netkit.classifiers.active.graphfunctions.LabelWeightedClosenessRank

toString() - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

toString() - Method in class netkit.classifiers.active.graphfunctions.WeightedBetweenness

toString() - Method in class netkit.classifiers.active.graphfunctions.WeightedCloseness

toString() - Method in class netkit.classifiers.active.PickLabelStrategy.LabelNode

toString() - Method in class netkit.classifiers.active.PickLabelStrategyImp

toString() - Method in class netkit.classifiers.aggregators.AggregatorByValueImp

toString() - Method in class netkit.classifiers.aggregators.AggregatorImp

toString() - Method in class netkit.classifiers.bayes.NaiveBayesMultinomial

toString() - Method in class netkit.classifiers.Classification

toString() - Method in class netkit.classifiers.DataSampler

toString() - Method in class netkit.classifiers.DataSplit

toString() - Method in class netkit.classifiers.DataView

toString() - Method in class netkit.classifiers.Estimate

toString(Node, Estimate, Classification) - Method in class netkit.classifiers.io.PrintEstimateWriter

The equivalent of a print, where the output has been set to a string to be returned.

toString(Node, Estimate) - Method in class netkit.classifiers.io.PrintEstimateWriter

The equivalent of a print, where the output has been set to a string to be returned.

toString() - Method in class netkit.classifiers.nonrelational.ClassPrior

toString() - Method in class netkit.classifiers.nonrelational.ExternalPrior

toString() - Method in class netkit.classifiers.nonrelational.LocalWeka

toString() - Method in class netkit.classifiers.nonrelational.MetaMultiplicative

toString() - Method in class netkit.classifiers.nonrelational.NullPrior

toString() - Method in class netkit.classifiers.nonrelational.UniformPrior

toString() - Method in class netkit.classifiers.relational.ClassDistribRelNeighbor

toString() - Method in class netkit.classifiers.relational.Harmonic

toString() - Method in class netkit.classifiers.relational.MetaMultiplicative

toString() - Method in class netkit.classifiers.relational.NetworkOnlyBayes

toString() - Method in class netkit.classifiers.relational.NetworkWeka

toString() - Method in class netkit.classifiers.relational.ProbRelationalNeighbor

toString() - Method in class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

toString() - Method in class netkit.graph.Attribute

Returns a String representation for this object.

toString() - Method in class netkit.graph.Attributes

Returns a String representation for this object.

toString() - Method in class netkit.graph.Edge

Returns a String representation for this object.

toString() - Method in class netkit.graph.EdgeType

Returns a String representation for this object.

toString() - Method in class netkit.graph.Node

Returns a String representation for this object.

toString(String) - Method in class netkit.util.Configuration

toString() - Method in class netkit.util.Configuration

toString() - Method in class netkit.util.ModularityClusterer.Cluster

trainAssortativity - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

transform(Graph, EdgeType) - Method in class netkit.EdgeTransformer

trueAssortativity - Variable in class netkit.graph.edgecreator.EdgeCreatorImp

type - Variable in class netkit.classifiers.aggregators.AggregatorImp

Type - Enum in netkit.graph

The enumeration of possible values of Attributes

U

UncertaintyLabeling - Class in netkit.classifiers.active

UncertaintyLabeling() - Constructor for class netkit.classifiers.active.UncertaintyLabeling

UniformPrior - Class in netkit.classifiers.nonrelational

Dummy classifier that always predicts that all classes were equally likely.

UniformPrior() - Constructor for class netkit.classifiers.nonrelational.UniformPrior

unknown - Variable in class netkit.inference.InferenceMethod

UpdatablePriorityQueue<E> - Class in netkit.util

UpdatablePriorityQueue() - Constructor for class netkit.util.UpdatablePriorityQueue

Creates a PriorityQueue with the default initial capacity (11) that orders its elements according to their natural ordering.

UpdatablePriorityQueue(int) - Constructor for class netkit.util.UpdatablePriorityQueue

Creates a PriorityQueue with the specified initial capacity that orders its elements according to their natural ordering.

UpdatablePriorityQueue(int, Comparator<? super E>) - Constructor for class netkit.util.UpdatablePriorityQueue

Creates a PriorityQueue with the specified initial capacity that orders its elements according to the specified comparator.

update(ModularityClusterer.Cluster, double, Node, Node[]) - Method in class netkit.classifiers.active.graphfunctions.ERMRank

update(ModularityClusterer.Cluster, double, Node, Node[]) - Method in class netkit.classifiers.active.graphfunctions.LabelClosenessRank

update(ModularityClusterer.Cluster, double, Node, Node[]) - Method in class netkit.classifiers.active.graphfunctions.LabelWeightedClosenessRank

update(ModularityClusterer.Cluster, double, Node, Node[]) - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

Return the new score of a node given its old score and a newly labeled node.

update(UpdatablePriorityQueue<E>.QueueElement) - Method in class netkit.util.UpdatablePriorityQueue

updateable() - Method in class netkit.classifiers.active.graphfunctions.ERMRank

updateable() - Method in class netkit.classifiers.active.graphfunctions.LabelClosenessRank

updateable() - Method in class netkit.classifiers.active.graphfunctions.LabelWeightedClosenessRank

updateable() - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

returns whether the score of a node will change if more nodes are labeled.

updateQueue(int, Queue<Integer>) - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

Update the queue with the current node, returning the first node index which was added (if any)

usage(String) - Static method in class netkit.classifiers.NetworkLearning

usage(String) - Static method in class netkit.EdgeTransformer

usage(String) - Static method in class netkit.GraphStat

usage() - Static method in class netkit.Netkit

useIntrinsic - Variable in class netkit.classifiers.ClassifierImp

V

validateSettings() - Method in class netkit.util.ApproximateCentralities.ApproximateCentrality

Validates settings such as alpha, delta, etc.

valueOf(String) - Static method in enum netkit.classifiers.relational.NetworkClassifierImp.Aggregation

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum netkit.graph.Type

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum netkit.util.LaplaceCorrection

Returns the enum constant of this type with the specified name.

values() - Static method in enum netkit.classifiers.relational.NetworkClassifierImp.Aggregation

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum netkit.graph.Type

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum netkit.util.LaplaceCorrection

Returns an array containing the constants of this enum type, in the order they are declared.

vectorClsIdx - Variable in class netkit.classifiers.ClassifierImp

VectorMath - Class in netkit.util

VectorMath() - Constructor for class netkit.util.VectorMath

W

weighted - Variable in class netkit.util.ApproximateCentralities.ApproximateCentrality

weightedAlphaCentrality - Variable in class netkit.util.ApproximateCentralities

WeightedBetweenness - Class in netkit.classifiers.active.graphfunctions

WeightedBetweenness() - Constructor for class netkit.classifiers.active.graphfunctions.WeightedBetweenness

WeightedCloseness - Class in netkit.classifiers.active.graphfunctions

WeightedCloseness() - Constructor for class netkit.classifiers.active.graphfunctions.WeightedCloseness

weightedPagerank - Variable in class netkit.util.ApproximateCentralities

WeightedVoteRelationalNeighbor - Class in netkit.classifiers.relational

weighted-vote Relational Neighbor Classifier (wvRN).

WeightedVoteRelationalNeighbor() - Constructor for class netkit.classifiers.relational.WeightedVoteRelationalNeighbor

worstScore() - Method in class netkit.classifiers.active.graphfunctions.ReverseScoringFunction

What is the best score (last to be picked)

worstScore() - Method in class netkit.classifiers.active.graphfunctions.ScoringFunction

What is the best score (last to be picked)

writeEdges(Edge[], Writer) - Static method in class netkit.graph.io.EdgeWriterRN

Writes Edges to the supplied Writer.

writeNodes(Node[], Writer) - Static method in class netkit.graph.io.NodeWriter

This static method does the work of writing output data for the class.

writeSchema(Graph, Writer, Map<String, String>, Map<String, String>) - Static method in class netkit.graph.io.SchemaWriter

Writes the Graph information in an extended ARFF format.

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