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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