Index (Mallet 2 API)

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absNorm() - Method in interface cc.mallet.types.ConstantMatrix
absNorm() - Method in class cc.mallet.types.DenseMatrix
absNorm(double[]) - Static method in class cc.mallet.types.MatrixOps
absNorm() - Method in class cc.mallet.types.SparseMatrixn
absNorm() - Method in class cc.mallet.types.SparseVector
absNormalize() - Method in class cc.mallet.types.DenseMatrix
absNormalize() - Method in interface cc.mallet.types.Matrix
absNormalize(double[]) - Static method in class cc.mallet.types.MatrixOps
absNormalize() - Method in class cc.mallet.types.SparseMatrixn
absoluteDifference(Dirichlet) - Method in class cc.mallet.types.Dirichlet: Compute the L1 residual between two dirichlets
AbstractBeliefPropagation - Class in cc.mallet.grmm.inference: Abstract base class for umplementations of belief propagation for general factor graphs.
AbstractBeliefPropagation() - Constructor for class cc.mallet.grmm.inference.AbstractBeliefPropagation
AbstractBeliefPropagation(AbstractBeliefPropagation.MessageStrategy) - Constructor for class cc.mallet.grmm.inference.AbstractBeliefPropagation
AbstractBeliefPropagation.AbstractMessageStrategy - Class in cc.mallet.grmm.inference
AbstractBeliefPropagation.AbstractMessageStrategy() - Constructor for class cc.mallet.grmm.inference.AbstractBeliefPropagation.AbstractMessageStrategy
AbstractBeliefPropagation.MaxProductMessageStrategy - Class in cc.mallet.grmm.inference
AbstractBeliefPropagation.MaxProductMessageStrategy() - Constructor for class cc.mallet.grmm.inference.AbstractBeliefPropagation.MaxProductMessageStrategy
AbstractBeliefPropagation.MessageStrategy - Interface in cc.mallet.grmm.inference
AbstractBeliefPropagation.SumProductMessageStrategy - Class in cc.mallet.grmm.inference
AbstractBeliefPropagation.SumProductMessageStrategy() - Constructor for class cc.mallet.grmm.inference.AbstractBeliefPropagation.SumProductMessageStrategy
AbstractBeliefPropagation.SumProductMessageStrategy(double) - Constructor for class cc.mallet.grmm.inference.AbstractBeliefPropagation.SumProductMessageStrategy
AbstractFactor - Class in cc.mallet.grmm.types: An Abstract class from which new Factor classes can be subclassed.
AbstractFactor() - Constructor for class cc.mallet.grmm.types.AbstractFactor
AbstractFactor(VarSet) - Constructor for class cc.mallet.grmm.types.AbstractFactor
AbstractInferencer - Class in cc.mallet.grmm.inference: Abstract base class for inferencers.
AbstractInferencer() - Constructor for class cc.mallet.grmm.inference.AbstractInferencer
AbstractMessageStrategy - Class in cc.mallet.grmm.inference.gbp: Created: May 29, 2005
AbstractMessageStrategy() - Constructor for class cc.mallet.grmm.inference.gbp.AbstractMessageStrategy
AbstractTableFactor - Class in cc.mallet.grmm.types: Class for a multivariate multinomial distribution.
AbstractTableFactor(BidirectionalIntObjectMap) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor
AbstractTableFactor(Variable) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates an identity potential over the given variable.
AbstractTableFactor(Variable, double[]) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor
AbstractTableFactor() - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates an identity potential over NO variables.
AbstractTableFactor(Variable[]) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates an identity potential with the given variables.
AbstractTableFactor(Collection) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates an identity potential with the given variables.
AbstractTableFactor(Variable[], double[]) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates a potential with the given variables and the given probabilities.
AbstractTableFactor(VarSet, double[]) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates a potential with the given variables and the given probabilities.
AbstractTableFactor(Variable[], Matrix) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates a potential with the given variables and the given probabilities.
AbstractTableFactor(AbstractTableFactor) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Copy constructor.
AbstractTableFactor(VarSet, Matrix) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates a potential with the given variables and the given probabilities.
AbstractTableFactor(AbstractTableFactor, double[]) - Constructor for class cc.mallet.grmm.types.AbstractTableFactor: Creates a potential with the same variables as another, but different probabilites.
accept(File) - Method in class cc.mallet.util.DirectoryFilter
accept(File) - Method in class cc.mallet.util.RegexFileFilter
accuracyAtCoverage(double) - Method in class cc.mallet.classify.evaluate.AccuracyCoverage: accuracy at a given coverage percentage
accuracyAtCoverage(double) - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator
AccuracyCoverage - Class in cc.mallet.classify.evaluate: Methods for calculating and displaying the accuracy v.
AccuracyCoverage(Trial, int, String, String) - Constructor for class cc.mallet.classify.evaluate.AccuracyCoverage: Constructs object, sorts classifications, and creates accuracyValues array
AccuracyCoverage(Trial, String, String) - Constructor for class cc.mallet.classify.evaluate.AccuracyCoverage
AccuracyCoverage(Trial, String) - Constructor for class cc.mallet.classify.evaluate.AccuracyCoverage
AccuracyCoverage(Classifier, InstanceList, String) - Constructor for class cc.mallet.classify.evaluate.AccuracyCoverage
AccuracyCoverage(Classifier, InstanceList, int, String) - Constructor for class cc.mallet.classify.evaluate.AccuracyCoverage
AccuracyCoverage.ClassificationComparator - Class in cc.mallet.classify.evaluate
AccuracyCoverage.ClassificationComparator() - Constructor for class cc.mallet.classify.evaluate.AccuracyCoverage.ClassificationComparator
AccuracyCoverageEvaluator - Class in cc.mallet.extract: Constructs Accuracy-coverage graph using confidence values to sort Fields.
AccuracyCoverageEvaluator(int) - Constructor for class cc.mallet.extract.AccuracyCoverageEvaluator
accuracyCoverageValuesToString() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator
AccuracyEvaluator - Class in cc.mallet.cluster.evaluate: Accuracy of a clustering is (truePositive + trueNegative) / (numberPairwiseComparisons)
AccuracyEvaluator() - Constructor for class cc.mallet.cluster.evaluate.AccuracyEvaluator
accuracyRecallValuesToString(int) - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator
accuracyValues() - Method in class cc.mallet.classify.evaluate.AccuracyCoverage
ACRF - Class in cc.mallet.grmm.learning: Class for Arbitrary CRFs.
ACRF(Pipe, ACRF.Template[]) - Constructor for class cc.mallet.grmm.learning.ACRF: Create a ACRF for a 1-d sequence.
ACRF.BigramTemplate - Class in cc.mallet.grmm.learning: A template that adds edges between adjacent nodes in a label sequence for one factor.
ACRF.BigramTemplate(int) - Constructor for class cc.mallet.grmm.learning.ACRF.BigramTemplate
ACRF.FixedFactorTemplate - Class in cc.mallet.grmm.learning
ACRF.FixedFactorTemplate() - Constructor for class cc.mallet.grmm.learning.ACRF.FixedFactorTemplate
ACRF.GraphPostProcessor - Interface in cc.mallet.grmm.learning: Interface for making global transformations to an unrolled graph after it has been generated.
ACRF.MaximizableACRF - Class in cc.mallet.grmm.learning
ACRF.MaximizableACRF(InstanceList) - Constructor for class cc.mallet.grmm.learning.ACRF.MaximizableACRF
ACRF.PairwiseFactorTemplate - Class in cc.mallet.grmm.learning: A template that adds edges between cotemporal nodes of a given pair of factors.
ACRF.PairwiseFactorTemplate(int, int) - Constructor for class cc.mallet.grmm.learning.ACRF.PairwiseFactorTemplate
ACRF.SequenceTemplate - Class in cc.mallet.grmm.learning: Abstract class for Templates that expect a (FeatureVectorSequence, LabelsSequence) for their instances.
ACRF.SequenceTemplate() - Constructor for class cc.mallet.grmm.learning.ACRF.SequenceTemplate
ACRF.Template - Class in cc.mallet.grmm.learning: A type of clique in the model.
ACRF.Template() - Constructor for class cc.mallet.grmm.learning.ACRF.Template
ACRF.UnigramTemplate - Class in cc.mallet.grmm.learning: A template that adds node potentials for a given factor.
ACRF.UnigramTemplate(int) - Constructor for class cc.mallet.grmm.learning.ACRF.UnigramTemplate
ACRF.UnrolledGraph - Class in cc.mallet.grmm.learning
ACRF.UnrolledGraph(Instance, ACRF.Template[], ACRF.Template[]) - Constructor for class cc.mallet.grmm.learning.ACRF.UnrolledGraph
ACRF.UnrolledGraph(Instance, ACRF.Template[], List, boolean) - Constructor for class cc.mallet.grmm.learning.ACRF.UnrolledGraph: Creates a graphical model for a given instance.
ACRF.UnrolledVarSet - Class in cc.mallet.grmm.learning: A clique in the unrolled graphical model (an instantiation of some Template).
ACRF.UnrolledVarSet(ACRF.UnrolledGraph, ACRF.Template, Variable[], FeatureVector) - Constructor for class cc.mallet.grmm.learning.ACRF.UnrolledVarSet
ACRFEvaluator - Class in cc.mallet.grmm.learning: Created: Sun Jan 25 23:28:45 2004
ACRFEvaluator() - Constructor for class cc.mallet.grmm.learning.ACRFEvaluator
ACRFExtractor - Class in cc.mallet.grmm.learning.extract: Created: Mar 1, 2005
ACRFExtractor(ACRF, Pipe, Pipe) - Constructor for class cc.mallet.grmm.learning.extract.ACRFExtractor
ACRFExtractorTrainer - Class in cc.mallet.grmm.learning.extract: Created: Mar 31, 2005
ACRFExtractorTrainer() - Constructor for class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer
AcrfExtractorTui - Class in cc.mallet.grmm.learning.extract
AcrfExtractorTui() - Constructor for class cc.mallet.grmm.learning.extract.AcrfExtractorTui
AcrfSerialEvaluator - Class in cc.mallet.grmm.learning: Created: Aug 24, 2005
AcrfSerialEvaluator(List) - Constructor for class cc.mallet.grmm.learning.AcrfSerialEvaluator
ACRFTrainer - Interface in cc.mallet.grmm.learning: $Id: ACRFTrainer.java,v 1.1 2007/10/22 21:37:43 mccallum Exp $
actionPerformed(ActionEvent) - Method in class cc.mallet.classify.evaluate.AccuracyCoverage
AdaBoost - Class in cc.mallet.classify: AdaBoost Robert E.
AdaBoost(Pipe, Classifier[], double[]) - Constructor for class cc.mallet.classify.AdaBoost
AdaBoostM2 - Class in cc.mallet.classify: AdaBoostM2
AdaBoostM2(Pipe, Classifier[], double[]) - Constructor for class cc.mallet.classify.AdaBoostM2
AdaBoostM2Trainer - Class in cc.mallet.classify: This version of AdaBoost can handle multi-class problems.
AdaBoostM2Trainer(ClassifierTrainer, int) - Constructor for class cc.mallet.classify.AdaBoostM2Trainer
AdaBoostM2Trainer(ClassifierTrainer) - Constructor for class cc.mallet.classify.AdaBoostM2Trainer
AdaBoostTrainer - Class in cc.mallet.classify: This version of AdaBoost should be used only for binary classification.
AdaBoostTrainer(ClassifierTrainer, int) - Constructor for class cc.mallet.classify.AdaBoostTrainer
AdaBoostTrainer(ClassifierTrainer) - Constructor for class cc.mallet.classify.AdaBoostTrainer
add(int, double, double, double) - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints.MaxEntL2IndGEConstraint
add(String) - Method in class cc.mallet.classify.evaluate.Graph.Legend
add(Classification) - Method in class cc.mallet.classify.Trial
add(int, Classification) - Method in class cc.mallet.classify.Trial
add(int, double, double, double) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints.OneLabelL2IndGEConstraint
add(int, double, double, int) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint
add(Object) - Method in class cc.mallet.grmm.types.BitVarSet
add(Object) - Method in class cc.mallet.grmm.types.HashVarSet
add(Object, boolean) - Method in class cc.mallet.grmm.types.HashVarSet
add(Object) - Method in class cc.mallet.grmm.types.ListVarSet
add(Object) - Method in class cc.mallet.grmm.types.Tree
add(Variable) - Method in class cc.mallet.grmm.types.Universe
add(Object) - Method in class cc.mallet.grmm.types.UnmodifiableVarSet
add(int, int, Object) - Method in class cc.mallet.grmm.util.CSIntInt2ObjectMultiMap
add(Object) - Method in class cc.mallet.grmm.util.THashMultiMap: Adds key as a key with an empty list as a value.
add(FeatureVector) - Method in class cc.mallet.types.AugmentableFeatureVector: Adds all indices that are present in some other feature vector with value 1.0.
add(FeatureVector, String) - Method in class cc.mallet.types.AugmentableFeatureVector: Adds all features from some other feature vector with weight 1.0.
add(FeatureVector, String, boolean) - Method in class cc.mallet.types.AugmentableFeatureVector: Adds all features from some other feature vector with weight 1.0.
add(int, double) - Method in class cc.mallet.types.AugmentableFeatureVector
add(Object, double) - Method in class cc.mallet.types.AugmentableFeatureVector
add(int) - Method in class cc.mallet.types.AugmentableFeatureVector
add(FeatureConjunction) - Method in class cc.mallet.types.FeatureConjunction.List
add(Object) - Method in class cc.mallet.types.FeatureSelection
add(int) - Method in class cc.mallet.types.FeatureSelection
add(int) - Method in class cc.mallet.types.FeatureSequence
add(Object) - Method in class cc.mallet.types.FeatureSequence
add(Object, Object, Object, Object, double) - Method in class cc.mallet.types.InstanceList: Deprecated. Use trainingset.addThruPipe (new Instance(data,target,name,source)) instead.
add(Object, Object, Object, Object) - Method in class cc.mallet.types.InstanceList: Deprecated. Use trainingset.add (new Instance(data,target,name,source)) instead.
add(Instance) - Method in class cc.mallet.types.InstanceList: Appends the instance to this list without passing the instance through the InstanceList's pipe.
add(Instance, double) - Method in class cc.mallet.types.InstanceList: Appends the instance to this list without passing it through this InstanceList's pipe, assigning it the specified weight.
add(int, Instance) - Method in class cc.mallet.types.InstanceList
add(Instance, double) - Method in class cc.mallet.types.MultiInstanceList
add(Instance) - Method in class cc.mallet.types.MultiInstanceList
add(int, Instance) - Method in class cc.mallet.types.MultiInstanceList
add(Instance) - Method in class cc.mallet.types.PagedInstanceList: Appends the instance to this list.
add(Classification) - Method in class cc.mallet.types.ROCData: Adds classification results to the ROC data
add(Trial) - Method in class cc.mallet.types.ROCData: Adds trial results to the ROC data
add(ROCData) - Method in class cc.mallet.types.ROCData: Adds existing ROC data to this ROC data
add(String) - Method in class cc.mallet.types.TokenSequence
add(Object) - Method in interface cc.mallet.util.Addable
add(CommandOption) - Method in class cc.mallet.util.CommandOption.List
add(CommandOption[]) - Method in class cc.mallet.util.CommandOption.List
add(CommandOption.List) - Method in class cc.mallet.util.CommandOption.List
add(Class) - Method in class cc.mallet.util.CommandOption.List
add(double) - Method in class cc.mallet.util.DoubleList
add(String, Object, PropertyList) - Static method in class cc.mallet.util.PropertyList
add(String, String, PropertyList) - Static method in class cc.mallet.util.PropertyList
add(String, double, PropertyList) - Static method in class cc.mallet.util.PropertyList
Addable - Interface in cc.mallet.util
addAll(Collection<? extends Classification>) - Method in class cc.mallet.classify.Trial
addAll(int, Collection<? extends Classification>) - Method in class cc.mallet.classify.Trial
addAll(Collection) - Method in class cc.mallet.grmm.types.HashVarSet
addAll(Collection) - Method in class cc.mallet.grmm.types.UnmodifiableVarSet
addAll(Collection<? extends Instance>) - Method in class cc.mallet.types.InstanceList
addAll(int, Collection<? extends Instance>) - Method in class cc.mallet.types.InstanceList
addAll(Object[]) - Method in class cc.mallet.types.TokenSequence
addAllFactors(FactorGraph, List) - Static method in class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator
AddClassifierTokenPredictions - Class in cc.mallet.pipe: This pipe uses a Classifier to label each token (i.e., using 0-th order Markov assumption), then adds the predictions as features to each token.
AddClassifierTokenPredictions(InstanceList) - Constructor for class cc.mallet.pipe.AddClassifierTokenPredictions
AddClassifierTokenPredictions(InstanceList, InstanceList) - Constructor for class cc.mallet.pipe.AddClassifierTokenPredictions
AddClassifierTokenPredictions(AddClassifierTokenPredictions.TokenClassifiers, int[], boolean, InstanceList) - Constructor for class cc.mallet.pipe.AddClassifierTokenPredictions
AddClassifierTokenPredictions.TokenClassifiers - Class in cc.mallet.pipe: This inner class represents the trained token classifiers.
AddClassifierTokenPredictions.TokenClassifiers(InstanceList) - Constructor for class cc.mallet.pipe.AddClassifierTokenPredictions.TokenClassifiers: Train a token classifier using the given Instances with 5-fold cross validation
AddClassifierTokenPredictions.TokenClassifiers(InstanceList, int, int) - Constructor for class cc.mallet.pipe.AddClassifierTokenPredictions.TokenClassifiers
AddClassifierTokenPredictions.TokenClassifiers(ClassifierTrainer, InstanceList, int, int) - Constructor for class cc.mallet.pipe.AddClassifierTokenPredictions.TokenClassifiers
addClique(ACRF.UnrolledVarSet) - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph
addConjunction(String, Alphabet, int[], boolean[]) - Method in class cc.mallet.pipe.AugmentableFeatureVectorAddConjunctions
addConstraint(int, double[], double) - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.classify.constraints.ge.MaxEntKLFLGEConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.classify.constraints.ge.MaxEntL2FLGEConstraints
addConstraint(int, int, double, double, double) - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.classify.constraints.pr.MaxEntL2FLPRConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelKLGEConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2GEConstraints
addConstraint(int, int, double, double, double) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints
addConstraint(int, double[][], double) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints
addConstraint(int, double[][], double) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelKLGEConstraints
addConstraint(int, double[][], double) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelL2GEConstraints
addConstraint(int, int, double, double) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints
addConstraint(int, double[], double) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints
addDataToGraph(double[], int, String) - Method in class cc.mallet.classify.evaluate.AccuracyCoverage
addDocumentExtraction(DocumentExtraction) - Method in class cc.mallet.extract.Extraction
addDocuments(InstanceList, int, int, int, String, Randoms) - Method in class cc.mallet.topics.LDA: Deprecated.
addEvaluator(TransducerEvaluator) - Method in class cc.mallet.fst.TransducerTrainer
addEvaluators(Collection<TransducerEvaluator>) - Method in class cc.mallet.fst.TransducerTrainer
addEvidence(FactorGraph, Assignment) - Static method in class cc.mallet.grmm.util.Models: Returns a new factor graph, the same as a given one, except that all the nodes in the given Assignment are clamped as evidence.
addEvidence(FactorGraph, Assignment, Map) - Static method in class cc.mallet.grmm.util.Models
addEvidence(UndirectedModel, Assignment) - Static method in class cc.mallet.grmm.util.Models
addExpectations(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints
addExpectations(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint
addExpectations(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints
addExpectations(double[]) - Method in interface cc.mallet.fst.semi_supervised.pr.constraints.PRConstraint
addFactor(Variable, Variable, double[]) - Method in class cc.mallet.grmm.types.FactorGraph
addFactor(Factor) - Method in class cc.mallet.grmm.types.FactorGraph: Adds a factor to the model.
addFactor(Factor) - Method in class cc.mallet.grmm.types.UndirectedModel
addFeaturesClassEntropyThreshold - Variable in class cc.mallet.classify.DecisionTree
addFeatureWeightsTo(double[]) - Method in class cc.mallet.types.FeatureSequence
addFeatureWeightsTo(double[], double) - Method in class cc.mallet.types.FeatureSequence
addFiller(LabeledSpan) - Method in class cc.mallet.extract.Field
addFixedPotential(ACRF.Template) - Method in class cc.mallet.grmm.learning.ACRF
addFixedPotentials(ACRF.Template[]) - Method in class cc.mallet.grmm.learning.ACRF
addFullyConnectedStates(String[]) - Method in class cc.mallet.fst.CRF: Add a group of states that are fully connected with each other, with parameters equal zero, and labels on their out-going arcs the same name as their destination state names.
addFullyConnectedStates(String[]) - Method in class cc.mallet.fst.HMM: Add a group of states that are fully connected with each other, with parameters equal zero, and labels on their out-going arcs the same name as their destination state names.
addFullyConnectedStatesForBiLabels() - Method in class cc.mallet.fst.CRF
addFullyConnectedStatesForBiLabels() - Method in class cc.mallet.fst.HMM
addFullyConnectedStatesForLabels() - Method in class cc.mallet.fst.CRF
addFullyConnectedStatesForLabels() - Method in class cc.mallet.fst.HMM
addFullyConnectedStatesForThreeQuarterLabels(InstanceList) - Method in class cc.mallet.fst.CRF
addFullyConnectedStatesForThreeQuarterLabels(InstanceList) - Method in class cc.mallet.fst.HMM
addFullyConnectedStatesForTriLabels() - Method in class cc.mallet.fst.CRF
addFullyConnectedStatesForTriLabels() - Method in class cc.mallet.fst.HMM
addInstances(InstanceList) - Method in class cc.mallet.topics.LDAHyper: Deprecated.
addInstances(InstanceList, List<LabelSequence>) - Method in class cc.mallet.topics.LDAHyper: Deprecated.
addInstances(InstanceList, int) - Method in class cc.mallet.topics.NPTopicModel
addInstances(InstanceList) - Method in class cc.mallet.topics.ParallelTopicModel
addInstances(InstanceList[]) - Method in class cc.mallet.topics.PolylingualTopicModel
addInstances(InstanceList) - Method in class cc.mallet.topics.SimpleLDA
addInstantiatedCliques(ACRF.UnrolledGraph, FeatureVectorSequence, LabelsAssignment) - Method in class cc.mallet.grmm.examples.CrossTemplate1
addInstantiatedCliques(ACRF.UnrolledGraph, FeatureVectorSequence, LabelsAssignment) - Method in class cc.mallet.grmm.learning.ACRF.BigramTemplate
addInstantiatedCliques(ACRF.UnrolledGraph, FeatureVectorSequence, LabelsAssignment) - Method in class cc.mallet.grmm.learning.ACRF.PairwiseFactorTemplate
addInstantiatedCliques(ACRF.UnrolledGraph, FeatureVectorSequence, LabelsAssignment) - Method in class cc.mallet.grmm.learning.ACRF.SequenceTemplate: Adds all instiated cliques for an instance.
addInstantiatedCliques(ACRF.UnrolledGraph, Instance) - Method in class cc.mallet.grmm.learning.ACRF.SequenceTemplate
addInstantiatedCliques(ACRF.UnrolledGraph, Instance) - Method in class cc.mallet.grmm.learning.ACRF.Template: Adds all instiated cliques for an instance.
addInstantiatedCliques(ACRF.UnrolledGraph, FeatureVectorSequence, LabelsAssignment) - Method in class cc.mallet.grmm.learning.ACRF.UnigramTemplate
addInstantiatedCliques(ACRF.UnrolledGraph, FeatureVectorSequence, LabelsAssignment) - Method in class cc.mallet.grmm.learning.templates.SimilarTokensTemplate
addItem(String, int, Color) - Method in class cc.mallet.classify.evaluate.Graph
addItem(String, int) - Method in class cc.mallet.classify.evaluate.Graph
addItemVector(Vector, String) - Method in class cc.mallet.classify.evaluate.Graph: Adds a new data series
addLogProbabilities(double[]) - Method in class cc.mallet.types.Multinomial.Logged
addMultinomial(Multinomial) - Method in class cc.mallet.types.Dirichlet.Estimator
addNode(Object, Object) - Method in class cc.mallet.grmm.inference.JunctionTree
addNode(Object, Object) - Method in class cc.mallet.grmm.types.Tree
addOrderNStates(InstanceList, int[], boolean[], String, Pattern, Pattern, boolean) - Method in class cc.mallet.fst.CRF: Assumes that the CRF's output alphabet contains Strings.
addOrderNStates(InstanceList, int[], boolean[], String, Pattern, Pattern, boolean) - Method in class cc.mallet.fst.HMM: Assumes that the HMM's output alphabet contains Strings.
addProbabilities(double[]) - Method in class cc.mallet.types.Multinomial.Logged
addProbabilitiesTo(double[]) - Method in class cc.mallet.types.Multinomial
addPrunedWordsToStoplist(SimpleTokenizer, int) - Method in class cc.mallet.pipe.FeatureCountPipe: Add all pruned words to the internal stoplist of a SimpleTokenizer.
addPrunedWordsToStoplist(SimpleTokenizer, double) - Method in class cc.mallet.pipe.FeatureDocFreqPipe: Add all pruned words to the internal stoplist of a SimpleTokenizer.
addRandomNodePotentials(Random, FactorGraph) - Static method in class cc.mallet.grmm.inference.RandomGraphs
addRow(Variable[], int[]) - Method in class cc.mallet.grmm.types.Assignment
addRow(Variable[], double[]) - Method in class cc.mallet.grmm.types.Assignment
addRow(Variable[], Object[]) - Method in class cc.mallet.grmm.types.Assignment
addRow(Object[]) - Method in class cc.mallet.grmm.types.Assignment
addRow(Assignment) - Method in class cc.mallet.grmm.types.Assignment
addSelfTransitioningStateForAllLabels(String) - Method in class cc.mallet.fst.CRF
addSelfTransitioningStateForAllLabels(String) - Method in class cc.mallet.fst.HMM
addSomeUnsupportedWeights(InstanceList) - Method in class cc.mallet.grmm.learning.ACRF.Template
addStartState() - Method in class cc.mallet.fst.CRF
addStartState(String) - Method in class cc.mallet.fst.CRF
addStartState(int) - Method in class cc.mallet.fst.semi_supervised.StateLabelMap: If there is a special start state in the CRF that is not included in the label set, then we need to add it here.
addState(String, double, double, String[], String[], String[][]) - Method in class cc.mallet.fst.CRF
addState(String, double, double, String[], String[], String[]) - Method in class cc.mallet.fst.CRF
addState(String, double, double, String[], String[]) - Method in class cc.mallet.fst.CRF: Default gives separate parameters to each transition.
addState(String, String[]) - Method in class cc.mallet.fst.CRF: Add a state with parameters equal zero, and labels on out-going arcs the same name as their destination state names.
addState(String, double, double, int[], int[], double[], String[]) - Method in class cc.mallet.fst.FeatureTransducer
addState(String, double, double, Object[], Object[], double[], String[]) - Method in class cc.mallet.fst.FeatureTransducer
addState(String, double, double, String[], String[]) - Method in class cc.mallet.fst.HMM
addState(String, String[]) - Method in class cc.mallet.fst.HMM: Add a state with parameters equal zero, and labels on out-going arcs the same name as their destination state names.
addState(String, String) - Method in class cc.mallet.fst.semi_supervised.StateLabelMap: Adds a state to the map.
addStatesForBiLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.CRF: Add states to create a second-order Markov model on labels, adding only those transitions the occur in the given trainingSet.
addStatesForBiLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.HMM: Add states to create a second-order Markov model on labels, adding only those transitions the occur in the given trainingSet.
addStatesForHalfLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.CRF: Add as many states as there are labels, but don't create separate weights for each source-destination pair of states.
addStatesForHalfLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.HMM: Add as many states as there are labels, but don't create separate weights for each source-destination pair of states.
addStatesForLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.CRF: Add states to create a first-order Markov model on labels, adding only those transitions the occur in the given trainingSet.
addStatesForLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.HMM: Add states to create a first-order Markov model on labels, adding only those transitions the occur in the given trainingSet.
addStatesForThreeQuarterLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.CRF: Add as many states as there are labels, but don't create separate observational-test-weights for each source-destination pair of states---instead have all the incoming transitions to a state share the same observational-feature-test weights.
addStatesForThreeQuarterLabelsConnectedAsIn(InstanceList) - Method in class cc.mallet.fst.HMM: Add as many states as there are labels, but don't create separate observational-test-weights for each source-destination pair of states---instead have all the incoming transitions to a state share the same observational-feature-test weights.
addStopWords(String[]) - Method in class cc.mallet.pipe.TokenSequenceRemoveStopwords
addStopWords(File) - Method in class cc.mallet.pipe.TokenSequenceRemoveStopwords: Add whitespace-separated tokens in file "wordlist" to the stoplist.
addThruPipe(Iterator<Instance>) - Method in class cc.mallet.types.InstanceList: Adds to this list every instance generated by the iterator, passing each one through this InstanceList's pipe.
addThruPipe(Instance) - Method in class cc.mallet.types.InstanceList: Adds the input instance to this list, after passing it through the InstanceList's pipe.
addTo(double[], double) - Method in class cc.mallet.types.AugmentableFeatureVector
addTo(double[]) - Method in class cc.mallet.types.AugmentableFeatureVector
addTo(double[]) - Method in class cc.mallet.types.DenseVector
addTo(double[], double) - Method in class cc.mallet.types.DenseVector
addTo(AugmentableFeatureVector, double, FeatureSelection) - Method in class cc.mallet.types.FeatureConjunction
addTo(AugmentableFeatureVector, double) - Method in class cc.mallet.types.FeatureConjunction
addTo(AugmentableFeatureVector) - Method in class cc.mallet.types.FeatureConjunction
addTo(AugmentableFeatureVector, double, FeatureSelection) - Method in class cc.mallet.types.FeatureConjunction.List
addTo(AugmentableFeatureVector, double) - Method in class cc.mallet.types.FeatureConjunction.List
addTo(double[]) - Method in class cc.mallet.types.Label
addTo(double[], double) - Method in class cc.mallet.types.Label
addTo(double[]) - Method in interface cc.mallet.types.Labeling
addTo(double[], double) - Method in interface cc.mallet.types.Labeling
addTo(double[], double) - Method in class cc.mallet.types.SparseVector
addTo(double[]) - Method in class cc.mallet.types.SparseVector
addToTopicScore(int, double) - Method in class cc.mallet.topics.TopicModelDiagnostics.TopicScores
addTrial(Trial, String) - Method in class cc.mallet.classify.evaluate.AccuracyCoverage
addTrial(Trial, int, String) - Method in class cc.mallet.classify.evaluate.AccuracyCoverage
addWeight(int, String) - Method in class cc.mallet.fst.CRF.State
advance() - Method in interface cc.mallet.grmm.types.AssignmentIterator
afterFactorAdd(Factor) - Method in class cc.mallet.grmm.types.DirectedModel
afterFactorAdd(Factor) - Method in class cc.mallet.grmm.types.FactorGraph: Performs operations on a factor after it has been added to the model, such as caching.
AgglomerativeNeighbor - Class in cc.mallet.cluster.neighbor_evaluator: A Neighbor created by merging two clusters of the original Clustering.
AgglomerativeNeighbor(Clustering, Clustering, int[][]) - Constructor for class cc.mallet.cluster.neighbor_evaluator.AgglomerativeNeighbor
AgglomerativeNeighbor(Clustering, Clustering, int[], int[]) - Constructor for class cc.mallet.cluster.neighbor_evaluator.AgglomerativeNeighbor
AgglomerativeNeighbor(Clustering, Clustering, int, int) - Constructor for class cc.mallet.cluster.neighbor_evaluator.AgglomerativeNeighbor
AGIS - Class in cc.mallet.optimize
AGIS(Optimizable.ByGISUpdate, double) - Constructor for class cc.mallet.optimize.AGIS
AGIS(Optimizable.ByGISUpdate, double, boolean) - Constructor for class cc.mallet.optimize.AGIS
algorithms - Variable in class cc.mallet.grmm.test.TestInference
ALL_DIRECTORIES - Static variable in class cc.mallet.pipe.iterator.FileIterator: Use as label names all the directory names in the filename.
ALL_DIRECTORIES - Static variable in class cc.mallet.pipe.iterator.FileListIterator: Use as label names all the directory names in the filename.
ALL_DIRECTORIES - Static variable in class cc.mallet.pipe.iterator.UnlabeledFileIterator: Use as label names all the directory names in the filename.
allAlgs - Variable in class cc.mallet.grmm.test.TestInference
allFactorsContaining(Collection) - Method in class cc.mallet.grmm.types.FactorGraph: Returns a collection of all factors that involve only the given variables.
allFactorsContaining(Variable) - Method in class cc.mallet.grmm.types.FactorGraph
allFactorsOf(Variable) - Method in class cc.mallet.grmm.types.FactorGraph: Returns a list of all factors in the graph whose domain is exactly the specified var.
allFactorsOf(Collection) - Method in class cc.mallet.grmm.types.FactorGraph: Returns a list of all factors in the graph whose domain is exactly the specified Collection of Variables.
allL1MarginalDistance(FactorGraph, Inferencer, Inferencer) - Static method in class cc.mallet.grmm.inference.Utils
AllPairsIterator - Class in cc.mallet.cluster.iterator: Iterate over all pairs of Instances.
AllPairsIterator(Clustering) - Constructor for class cc.mallet.cluster.iterator.AllPairsIterator
almostEquals(Factor) - Method in class cc.mallet.grmm.types.AbstractFactor
almostEquals(Factor) - Method in class cc.mallet.grmm.types.AbstractTableFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.AbstractTableFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.Assignment
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.BetaFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.BinaryUnaryFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.BoltzmannPairFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.BoltzmannUnaryFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.ConstantFactor
almostEquals(Factor) - Method in class cc.mallet.grmm.types.CPT
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.CPT
almostEquals(Factor) - Method in interface cc.mallet.grmm.types.Factor: Returns whether this is almost equal to another potential.
almostEquals(Factor, double) - Method in interface cc.mallet.grmm.types.Factor
almostEquals(Factor) - Method in class cc.mallet.grmm.types.FactorGraph
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.FactorGraph
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.NormalFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.PottsTableFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.SkeletonFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.UniformFactor
almostEquals(Factor, double) - Method in class cc.mallet.grmm.types.UniNormalFactor
almostEquals(ConstantMatrix) - Method in class cc.mallet.types.DenseMatrix
almostEquals(double, double) - Static method in class cc.mallet.util.Maths
almostEquals(double, double, double) - Static method in class cc.mallet.util.Maths
almostEquals(double[], double[], double) - Static method in class cc.mallet.util.Maths
alpha - Variable in class cc.mallet.fst.semi_supervised.EntropyLattice.LatticeNode
alpha - Variable in class cc.mallet.fst.semi_supervised.GELattice.LatticeNode
alpha - Variable in class cc.mallet.topics.LDAHyper: Deprecated.
alpha - Variable in class cc.mallet.topics.MarginalProbEstimator
alpha - Variable in class cc.mallet.topics.NPTopicModel
alpha - Variable in class cc.mallet.topics.ParallelTopicModel
alpha - Variable in class cc.mallet.topics.PolylingualTopicModel
alpha - Variable in class cc.mallet.topics.SimpleLDA
alpha - Variable in class cc.mallet.topics.TopicInferencer
alpha - Variable in class cc.mallet.topics.WorkerRunnable
alpha(int) - Method in class cc.mallet.types.Dirichlet
alphabet - Variable in class cc.mallet.grmm.learning.DefaultAcrfTrainer.TestResults
alphabet - Variable in class cc.mallet.topics.LDAHyper: Deprecated.
alphabet - Variable in class cc.mallet.topics.NPTopicModel
alphabet - Variable in class cc.mallet.topics.ParallelTopicModel
alphabet - Variable in class cc.mallet.topics.SimpleLDA
Alphabet - Class in cc.mallet.types: A mapping between integers and objects where the mapping in each direction is efficient.
Alphabet(int, Class) - Constructor for class cc.mallet.types.Alphabet
Alphabet(Class) - Constructor for class cc.mallet.types.Alphabet
Alphabet(int) - Constructor for class cc.mallet.types.Alphabet
Alphabet() - Constructor for class cc.mallet.types.Alphabet
Alphabet(Object[]) - Constructor for class cc.mallet.types.Alphabet
AlphabetCarrying - Interface in cc.mallet.types: An interface for objects that contain one or more Alphabets.
AlphabetFactory - Class in cc.mallet.types
AlphabetFactory() - Constructor for class cc.mallet.types.AlphabetFactory
alphabetOfSize(int) - Static method in class cc.mallet.types.AlphabetFactory: Create a dummy alphabet with n dimensions
alphabets - Variable in class cc.mallet.topics.PolylingualTopicModel
alphabetsMatch(AlphabetCarrying) - Method in class cc.mallet.classify.Classifier
alphabetsMatch(AlphabetCarrying) - Method in class cc.mallet.classify.NaiveBayesTrainer
alphabetsMatch(AlphabetCarrying) - Method in class cc.mallet.pipe.Pipe
alphabetsMatch(AlphabetCarrying, AlphabetCarrying) - Static method in class cc.mallet.types.Alphabet: Convenience method that can often implement alphabetsMatch in classes that implement the AlphabetsCarrying interface.
alphabetsMatch(AlphabetCarrying) - Method in class cc.mallet.types.FeatureSequence
alphabetsMatch(AlphabetCarrying) - Method in class cc.mallet.types.FeatureVector
alphabetsMatch(AlphabetCarrying) - Method in class cc.mallet.types.Instance
alphaSum - Variable in class cc.mallet.topics.LDAHyper: Deprecated.
alphaSum - Variable in class cc.mallet.topics.MarginalProbEstimator
alphaSum - Variable in class cc.mallet.topics.ParallelTopicModel
alphaSum - Variable in class cc.mallet.topics.PolylingualTopicModel
alphaSum - Variable in class cc.mallet.topics.SimpleLDA
alphaSum - Variable in class cc.mallet.topics.WorkerRunnable
any(TDoubleProcedure, double[]) - Static method in class cc.mallet.util.ArrayUtils: Returns true if the procedure proc returns true for any element of the array v.
any(TObjectProcedure, Object[][]) - Static method in class cc.mallet.util.ArrayUtils: Returns true if the procedure proc returns true for any element of the array v.
append(double[], double) - Static method in class cc.mallet.types.MatrixOps
append(int[], int[]) - Static method in class cc.mallet.util.ArrayUtils: Returns a new array that is the concatenation of a1 and a2.
append(double[], double[]) - Static method in class cc.mallet.util.ArrayUtils: Returns a new array that is the concatenation of a1 and a2.
append(int[], int) - Static method in class cc.mallet.util.ArrayUtils: Returns a new array with a single element appended at the end.
append(boolean[], boolean) - Static method in class cc.mallet.util.ArrayUtils: Returns a new array with a single element appended at the end.
append(Object[], Object) - Static method in class cc.mallet.util.ArrayUtils: Returns a new array with a single element appended at the end.
append(PropertyList) - Method in class cc.mallet.util.PropertyList
apply(Transducer, Sequence, int) - Static method in class cc.mallet.fst.semi_supervised.tui.SimpleTaggerWithConstraints: Apply a transducer to an input sequence to produce the k highest-scoring output sequences.
apply(Transducer, Sequence, int) - Static method in class cc.mallet.fst.SimpleTagger: Apply a transducer to an input sequence to produce the k highest-scoring output sequences.
appxAlgs - Variable in class cc.mallet.grmm.test.TestInference
argmax() - Method in class cc.mallet.grmm.types.AbstractFactor
argmax() - Method in class cc.mallet.grmm.types.AbstractTableFactor
argmax() - Method in class cc.mallet.grmm.types.CPT
argmax() - Method in interface cc.mallet.grmm.types.Factor: Returns the assignment that maximizes this potential.
argmax() - Method in class cc.mallet.grmm.types.FactorGraph
argmax(double[]) - Static method in class cc.mallet.util.ArrayUtils
argmax(TObjectDoubleHashMap) - Static method in class cc.mallet.util.CollectionUtils: Returns the key in map that has the greatest score
Array2FeatureVector - Class in cc.mallet.pipe: Converts a Java array of numerical types to a FeatureVector, where the Alphabet is the data array index wrapped in an Integer object.
Array2FeatureVector(int) - Constructor for class cc.mallet.pipe.Array2FeatureVector
Array2FeatureVector() - Constructor for class cc.mallet.pipe.Array2FeatureVector
Array2FeatureVector(Alphabet, Alphabet) - Constructor for class cc.mallet.pipe.Array2FeatureVector: Construct a pipe based on the dimensions of the data and target.
arrayCopyFrom(int, Matrix) - Method in class cc.mallet.types.DenseVector
arrayCopyFrom(double[]) - Method in class cc.mallet.types.DenseVector: Copy values from an array into this vector.
arrayCopyFrom(double[], int) - Method in class cc.mallet.types.DenseVector: Copy values from an array starting at a particular index into this vector.
arrayCopyFrom(double[], int) - Method in class cc.mallet.types.Matrix2: Deprecated.
arrayCopyFrom(double[]) - Method in class cc.mallet.types.SparseVector: Copy values from an array into this vector.
arrayCopyFrom(double[], int) - Method in class cc.mallet.types.SparseVector: Copy values from an array starting at a particular location into this vector.
arrayCopyInto(double[], int) - Method in class cc.mallet.types.DenseVector: Copy the contents of this vector into an array starting at a particular index.
arrayCopyInto(double[], int) - Method in class cc.mallet.types.Matrix2: Deprecated.
arrayCopyInto(double[], int) - Method in class cc.mallet.types.SparseVector: Copy the contents of this vector into an array starting at a particular location.
arrayCopyTo(int, Matrix) - Method in class cc.mallet.types.DenseVector
arrayCopyTo(int, double[]) - Method in class cc.mallet.types.DenseVector
ArrayDataAndTargetIterator - Class in cc.mallet.pipe.iterator
ArrayDataAndTargetIterator(List, List) - Constructor for class cc.mallet.pipe.iterator.ArrayDataAndTargetIterator
ArrayDataAndTargetIterator(Object[], Object[]) - Constructor for class cc.mallet.pipe.iterator.ArrayDataAndTargetIterator
ArrayIterator - Class in cc.mallet.pipe.iterator
ArrayIterator(List, Object) - Constructor for class cc.mallet.pipe.iterator.ArrayIterator
ArrayIterator(List) - Constructor for class cc.mallet.pipe.iterator.ArrayIterator
ArrayIterator(Object[], Object) - Constructor for class cc.mallet.pipe.iterator.ArrayIterator
ArrayIterator(Object[]) - Constructor for class cc.mallet.pipe.iterator.ArrayIterator
ArrayListSequence<E> - Class in cc.mallet.types
ArrayListSequence() - Constructor for class cc.mallet.types.ArrayListSequence
ArrayListUtils - Class in cc.mallet.util
ArrayListUtils() - Constructor for class cc.mallet.util.ArrayListUtils
ArraySequence<E> - Class in cc.mallet.types
ArraySequence(ArrayList<E>) - Constructor for class cc.mallet.types.ArraySequence
ArraySequence(E[], boolean) - Constructor for class cc.mallet.types.ArraySequence
ArraySequence(E[]) - Constructor for class cc.mallet.types.ArraySequence
ArraySequence(Sequence<E>, boolean) - Constructor for class cc.mallet.types.ArraySequence
ArrayUtils - Class in cc.mallet.util: Static utility methods for arrays (like java.util.Arrays, but more useful).
asFactor(Inferencer) - Static method in class cc.mallet.grmm.types.Factors: Adapter that allows an Inferencer to be treated as if it were a factor.
asJavaRandom() - Method in class cc.mallet.util.Randoms: Deprecated.
asList() - Method in class cc.mallet.grmm.types.Assignment: Returns a list of single-row assignments, one for each row in this assignment.
assertNotNaN() - Method in class cc.mallet.fst.CRF.Factors
assertNotNaNOrInfinite() - Method in class cc.mallet.fst.CRF.Factors
assignedVertexPtls - Variable in class cc.mallet.grmm.inference.AbstractBeliefPropagation
Assignment - Class in cc.mallet.grmm.types: An assignment to a bunch of variables.
Assignment() - Constructor for class cc.mallet.grmm.types.Assignment: Creates an empty assignment.
Assignment(Variable, int) - Constructor for class cc.mallet.grmm.types.Assignment
Assignment(Variable, double) - Constructor for class cc.mallet.grmm.types.Assignment
Assignment(Variable[], int[]) - Constructor for class cc.mallet.grmm.types.Assignment: Creates an assignemnt for the given variables.
Assignment(Variable[], double[]) - Constructor for class cc.mallet.grmm.types.Assignment: Creates an assignemnt for the given variables.
Assignment(List, int[]) - Constructor for class cc.mallet.grmm.types.Assignment: Creates an assignemnt for the given variables.
Assignment(FactorGraph, int[]) - Constructor for class cc.mallet.grmm.types.Assignment: Creates an assignment over all Variables in a model.
assignment() - Method in interface cc.mallet.grmm.types.AssignmentIterator
assignmentIterator() - Method in class cc.mallet.grmm.types.AbstractFactor
assignmentIterator() - Method in class cc.mallet.grmm.types.AbstractTableFactor
AssignmentIterator - Interface in cc.mallet.grmm.types: Iterates over the assignments to a set of variables.
assignmentIterator() - Method in class cc.mallet.grmm.types.BitVarSet
assignmentIterator() - Method in class cc.mallet.grmm.types.CPT
assignmentIterator() - Method in interface cc.mallet.grmm.types.Factor: Returns an iterator over all Assignmentss to this potential.
assignmentIterator() - Method in class cc.mallet.grmm.types.FactorGraph: Returns an iterator over all assignments to all variables of this graphical model.
assignmentIterator() - Method in class cc.mallet.grmm.types.HashVarSet
assignmentIterator() - Method in class cc.mallet.grmm.types.ListVarSet
assignmentIterator() - Method in class cc.mallet.grmm.types.UnmodifiableVarSet
assignmentIterator() - Method in interface cc.mallet.grmm.types.VarSet: Returns an iterator over the assignments to this clique.
asTable() - Method in class cc.mallet.grmm.types.AbstractFactor
asTable() - Method in class cc.mallet.grmm.types.AbstractTableFactor
asTable() - Method in class cc.mallet.grmm.types.Assignment
asTable() - Method in class cc.mallet.grmm.types.CPT
asTable() - Method in interface cc.mallet.grmm.types.Factor
asTable() - Method in class cc.mallet.grmm.types.FactorGraph
AStar - Class in cc.mallet.util.search: Created by IntelliJ IDEA.
AStar(AStarState[], int) - Constructor for class cc.mallet.util.search.AStar: Create an A* search iterator starting from the given initial states.
AStarNode - Class in cc.mallet.util.search: Created by IntelliJ IDEA.
AStarNode(AStarState, AStarNode, double) - Constructor for class cc.mallet.util.search.AStarNode: Create an A* search node with given state, parent, and cost.
AStarNode.NextNodeIterator - Class in cc.mallet.util.search: Iterator over new A* search nodes generated by state transitions from this node's state.
AStarNode.NextNodeIterator() - Constructor for class cc.mallet.util.search.AStarNode.NextNodeIterator
AStarState - Interface in cc.mallet.util.search: Created by IntelliJ IDEA.
AugmentableFeatureVector - Class in cc.mallet.types
AugmentableFeatureVector(Alphabet, int[], double[], int, int, boolean, boolean, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector: To make a binary vector, pass null for "values"
AugmentableFeatureVector(Alphabet, int[], double[], int, boolean, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, int[], double[], int, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, int[], double[], int) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, double[], int) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, double[]) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, int, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(FeatureVector) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(FeatureSequence, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, PropertyList, boolean, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVector(Alphabet, PropertyList, boolean) - Constructor for class cc.mallet.types.AugmentableFeatureVector
AugmentableFeatureVectorAddConjunctions - Class in cc.mallet.pipe: Add specified conjunctions to each instance.
AugmentableFeatureVectorAddConjunctions() - Constructor for class cc.mallet.pipe.AugmentableFeatureVectorAddConjunctions
AugmentableFeatureVectorLogScale - Class in cc.mallet.pipe: Given an AugmentableFeatureVector, set those values greater than or equal to 1 to log(value)+1.
AugmentableFeatureVectorLogScale() - Constructor for class cc.mallet.pipe.AugmentableFeatureVectorLogScale
auxModel - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
average(Factor, Factor, double) - Static method in class cc.mallet.grmm.types.Factors
averageMessages(RegionGraph, MessageArray, MessageArray, double) - Method in class cc.mallet.grmm.inference.gbp.FullMessageStrategy
averageMessages(RegionGraph, MessageArray, MessageArray, double) - Method in interface cc.mallet.grmm.inference.gbp.MessageStrategy
averageMessages(RegionGraph, MessageArray, MessageArray, double) - Method in class cc.mallet.grmm.inference.gbp.SparseMessageSender
averageTokenAccuracy(InstanceList) - Method in class cc.mallet.fst.Transducer: Runs inference across all the instances and returns the average token accuracy.
avgL1MarginalDistance(FactorGraph, Inferencer, Inferencer) - Static method in class cc.mallet.grmm.inference.Utils

B

BackTrackLineSearch - Class in cc.mallet.optimize
BackTrackLineSearch(Optimizable.ByGradientValue) - Constructor for class cc.mallet.optimize.BackTrackLineSearch
backwardLattice(double[][], double[][][]) - Method in class cc.mallet.fst.semi_supervised.EntropyLattice: Computes the backward entropies (H^beta).
BaggingClassifier - Class in cc.mallet.classify
BaggingClassifier(Pipe, Classifier[]) - Constructor for class cc.mallet.classify.BaggingClassifier
BaggingTrainer - Class in cc.mallet.classify: Bagging Trainer.
BaggingTrainer(ClassifierTrainer.Factory, int) - Constructor for class cc.mallet.classify.BaggingTrainer
BaggingTrainer(ClassifierTrainer.Factory) - Constructor for class cc.mallet.classify.BaggingTrainer
BalancedWinnow - Class in cc.mallet.classify: Classification methods of BalancedWinnow algorithm.
BalancedWinnow(Pipe, double[][]) - Constructor for class cc.mallet.classify.BalancedWinnow: Passes along data pipe and weights from BalancedWinnowTrainer
BalancedWinnowTrainer - Class in cc.mallet.classify: An implementation of the training methods of a BalancedWinnow on-line classifier.
BalancedWinnowTrainer() - Constructor for class cc.mallet.classify.BalancedWinnowTrainer: Default constructor.
BalancedWinnowTrainer(double, double, int, double) - Constructor for class cc.mallet.classify.BalancedWinnowTrainer
bandCholesky(double[], int) - Static method in class cc.mallet.util.MVNormal
bandMatrixRoot(int, int) - Static method in class cc.mallet.util.MVNormal: For testing band cholesky factorization
batchCachedGradient - Variable in class cc.mallet.fst.ThreadedOptimizable: Gradient obtained from the optimizable for each batch
batchCachedValue - Variable in class cc.mallet.fst.ThreadedOptimizable: Value obtained from the optimizable for each batch
batchTest(InstanceList, List<Sequence>, String, PrintStream) - Method in class cc.mallet.fst.MultiSegmentationEvaluator: Tests segmentation using an ArrayList of predicted Sequences instead of a Transducer.
BCubedEvaluator - Class in cc.mallet.cluster.evaluate: Evaluate a Clustering using the B-Cubed evaluation metric.
BCubedEvaluator() - Constructor for class cc.mallet.cluster.evaluate.BCubedEvaluator
beamWidth - Static variable in class cc.mallet.fst.SumLatticeBeam
beforeFactorAdd(Factor) - Method in class cc.mallet.grmm.types.DirectedModel
beforeFactorAdd(Factor) - Method in class cc.mallet.grmm.types.FactorGraph: Performs checking of a factor before it is added to the model.
bestAssignment() - Method in class cc.mallet.grmm.inference.TRP
bestAssignment(InstanceList) - Method in class cc.mallet.grmm.learning.ACRF
bestAssignment(Instance) - Method in class cc.mallet.grmm.learning.ACRF
bestAssignment(FactorGraph, Inferencer) - Static method in class cc.mallet.grmm.util.Models: Returns the highest-score Assignment in a model according to a given inferencer.
bestLabelIsCorrect() - Method in class cc.mallet.classify.Classification
bestOutputAlignment() - Method in class cc.mallet.fst.MaxLatticeDefault
bestOutputAlignments(int) - Method in class cc.mallet.fst.MaxLatticeDefault
bestOutputSequence() - Method in interface cc.mallet.fst.MaxLattice
bestOutputSequence() - Method in class cc.mallet.fst.MaxLatticeDefault
bestOutputSequences(int) - Method in interface cc.mallet.fst.MaxLattice
bestOutputSequences(int) - Method in class cc.mallet.fst.MaxLatticeDefault
bestStateAlignment() - Method in class cc.mallet.fst.MaxLatticeDefault
bestStateAlignments(int) - Method in class cc.mallet.fst.MaxLatticeDefault: Perform the backward pass of Viterbi, returning the n-best sequences of States.
bestStateSequence() - Method in interface cc.mallet.fst.MaxLattice
bestStateSequence() - Method in class cc.mallet.fst.MaxLatticeDefault
bestStateSequences(int) - Method in interface cc.mallet.fst.MaxLattice
bestStateSequences(int) - Method in class cc.mallet.fst.MaxLatticeDefault
bestViterbiNodeSequences(int) - Method in class cc.mallet.fst.MaxLatticeDefault: Perform the backward pass of Viterbi, returning the n-best sequences of ViterbiNodes.
bestWeight() - Method in class cc.mallet.fst.MaxLatticeDefault
beta - Variable in class cc.mallet.fst.semi_supervised.EntropyLattice.LatticeNode
beta - Variable in class cc.mallet.fst.semi_supervised.GELattice.LatticeNode
beta - Variable in class cc.mallet.topics.LDAHyper: Deprecated.
beta - Variable in class cc.mallet.topics.MarginalProbEstimator
beta - Variable in class cc.mallet.topics.NPTopicModel
beta - Variable in class cc.mallet.topics.ParallelTopicModel
beta - Variable in class cc.mallet.topics.SimpleLDA
beta - Variable in class cc.mallet.topics.TopicInferencer
beta - Variable in class cc.mallet.topics.WorkerRunnable
beta(double, double) - Static method in class cc.mallet.util.Maths
BetaFactor - Class in cc.mallet.grmm.types: $Id: BetaFactor.java,v 1.1 2007/10/22 21:37:44 mccallum Exp $
BetaFactor(Variable, double, double) - Constructor for class cc.mallet.grmm.types.BetaFactor
BetaFactor(Variable, double, double, double, double) - Constructor for class cc.mallet.grmm.types.BetaFactor
betainv(double, double, double) - Static method in class cc.mallet.util.StatFunctions
betas - Variable in class cc.mallet.topics.PolylingualTopicModel
betaSum - Variable in class cc.mallet.topics.LDAHyper: Deprecated.
betaSum - Variable in class cc.mallet.topics.MarginalProbEstimator
betaSum - Variable in class cc.mallet.topics.NPTopicModel
betaSum - Variable in class cc.mallet.topics.ParallelTopicModel
betaSum - Variable in class cc.mallet.topics.SimpleLDA
betaSum - Variable in class cc.mallet.topics.TopicInferencer
betaSum - Variable in class cc.mallet.topics.WorkerRunnable
betaSums - Variable in class cc.mallet.topics.PolylingualTopicModel
between(double, double) - Method in class cc.mallet.util.Univariate
BidirectionalIntObjectMap - Class in cc.mallet.grmm.types: A mapping between integers and objects where the mapping in each direction is efficient.
BidirectionalIntObjectMap(int) - Constructor for class cc.mallet.grmm.types.BidirectionalIntObjectMap
BidirectionalIntObjectMap() - Constructor for class cc.mallet.grmm.types.BidirectionalIntObjectMap
BidirectionalIntObjectMap(BidirectionalIntObjectMap) - Constructor for class cc.mallet.grmm.types.BidirectionalIntObjectMap
BINARY_COUNT - Static variable in class cc.mallet.pipe.tsf.CountMatches
BinaryUnaryFactor - Class in cc.mallet.grmm.types: A factor over a continuous variable theta and binary variables var.
BinaryUnaryFactor(Variable, Variable, Variable) - Constructor for class cc.mallet.grmm.types.BinaryUnaryFactor
BIOTokenizationFilter - Class in cc.mallet.extract: Created: Nov 12, 2004
BIOTokenizationFilter() - Constructor for class cc.mallet.extract.BIOTokenizationFilter
BIOTokenizationFilterWithTokenIndices - Class in cc.mallet.extract
BIOTokenizationFilterWithTokenIndices() - Constructor for class cc.mallet.extract.BIOTokenizationFilterWithTokenIndices
BitVarSet - Class in cc.mallet.grmm.types: A clique that uses very little time and memory based on the flyweight pattern.
BitVarSet(Universe, BitSet) - Constructor for class cc.mallet.grmm.types.BitVarSet: Creates a BitSet clique given an alphabet of Variables, and a bitset that says which variables in the alphabet to include in the clique.
BitVarSet(Universe, Collection) - Constructor for class cc.mallet.grmm.types.BitVarSet
BitVarSet(VarSet) - Constructor for class cc.mallet.grmm.types.BitVarSet
BoltzmannPairFactor - Class in cc.mallet.grmm.types: A factor over a continuous variable theta and binary variables var.
BoltzmannPairFactor(Variable, Variable, double) - Constructor for class cc.mallet.grmm.types.BoltzmannPairFactor
BoltzmannUnaryFactor - Class in cc.mallet.grmm.types: A factor over a continuous variable theta and binary variables var.
BoltzmannUnaryFactor(Variable, double) - Constructor for class cc.mallet.grmm.types.BoltzmannUnaryFactor
Boostable - Interface in cc.mallet.classify: This interface is a tag indicating that the classifier attends to the InstanceList.getInstanceWeight() weights when training.
BPRegionGenerator - Class in cc.mallet.grmm.inference.gbp: Created: May 30, 2005
BPRegionGenerator() - Constructor for class cc.mallet.grmm.inference.gbp.BPRegionGenerator
BranchingPipe - Class in cc.mallet.pipe: Deprecated.
BranchingPipe() - Constructor for class cc.mallet.pipe.BranchingPipe: Deprecated.
BranchingPipe(Pipe[]) - Constructor for class cc.mallet.pipe.BranchingPipe: Deprecated.
BranchingPipe(Collection<Pipe>) - Constructor for class cc.mallet.pipe.BranchingPipe: Deprecated.
BruteForceInferencer - Class in cc.mallet.grmm.inference: Computes the joint of a GraphicalModel by brute-force calculation.
BruteForceInferencer() - Constructor for class cc.mallet.grmm.inference.BruteForceInferencer
BshInterpreter - Class in cc.mallet.util
BshInterpreter(String) - Constructor for class cc.mallet.util.BshInterpreter
BshInterpreter() - Constructor for class cc.mallet.util.BshInterpreter
buildInitialTypeTopicCounts() - Method in class cc.mallet.topics.ParallelTopicModel
buildJunctionTree(FactorGraph) - Method in class cc.mallet.grmm.inference.JunctionTreeInferencer: Constructs a junction tree from a given factor graph.
buildLocalTypeTopicCounts() - Method in class cc.mallet.topics.WorkerRunnable: Once we have sampled the local counts, trash the "global" type topic counts and reuse the space to build a summary of the type topic counts specific to this worker's section of the corpus.
BulkLoader - Class in cc.mallet.util: This class reads through a single file, breaking each line into data and (optional) name and label fields.
BulkLoader() - Constructor for class cc.mallet.util.BulkLoader
burninPeriod - Variable in class cc.mallet.topics.LDAHyper: Deprecated.
burninPeriod - Variable in class cc.mallet.topics.ParallelTopicModel
burninPeriod - Variable in class cc.mallet.topics.PolylingualTopicModel
BY_EDGE - Static variable in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer: Use per-edge structured pseudolikelihood.
BY_VARIABLE - Static variable in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer: Use per-variable pseudolikelihood.

C

C45 - Class in cc.mallet.classify: A C4.5 Decision Tree classifier.
C45(Pipe, C45.Node) - Constructor for class cc.mallet.classify.C45
C45.Node - Class in cc.mallet.classify
C45.Node(InstanceList, C45.Node, int) - Constructor for class cc.mallet.classify.C45.Node
C45.Node(InstanceList, C45.Node, int, int[]) - Constructor for class cc.mallet.classify.C45.Node
C45Trainer - Class in cc.mallet.classify: A C4.5 decision tree learner, approximtely.
C45Trainer() - Constructor for class cc.mallet.classify.C45Trainer: Uses default values: not depth limited tree with a minimum of 2 instances in each leaf node
C45Trainer(int) - Constructor for class cc.mallet.classify.C45Trainer: Construct a depth-limited tree with the given depth limit
C45Trainer(boolean) - Constructor for class cc.mallet.classify.C45Trainer
C45Trainer(int, boolean) - Constructor for class cc.mallet.classify.C45Trainer
cache - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints
cache - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints
cache - Variable in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints
cache - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints
cache - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints
cachedCoefficients - Variable in class cc.mallet.topics.LDAHyper: Deprecated.
cachedCoefficients - Variable in class cc.mallet.topics.MarginalProbEstimator
cachedCoefficients - Variable in class cc.mallet.topics.WorkerRunnable
cachedDots - Variable in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
CachedDotTransitionIterator - Class in cc.mallet.fst.semi_supervised.pr: TransitionIterator that caches dot products.
CachedDotTransitionIterator(CRF.State, Sequence, int, String, double[]) - Constructor for class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator
CachedDotTransitionIterator(CRF.State, Object, String, double[]) - Constructor for class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator
cachedGradient - Variable in class cc.mallet.classify.MaxEntOptimizableByGE
cachedGradient - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
cachedGradient - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood
cachedGradient - Variable in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization
cachedGradient - Variable in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
cachedGradient - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
cachedGradientChangeStamp - Variable in class cc.mallet.fst.CRFCacheStaleIndicator
cachedGradientWeightsStamp - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
CachedMetric - Interface in cc.mallet.types: Stores a hash for each object being compared for efficient computation.
cachedNumParametersStamp - Variable in class cc.mallet.fst.CRF
cacheDotProducts() - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
cachedValue - Variable in class cc.mallet.classify.MaxEntOptimizableByGE
cachedValue - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
cachedValue - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood
cachedValue - Variable in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization
cachedValue - Variable in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
cachedValue - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
cachedValueChangeStamp - Variable in class cc.mallet.fst.CRFCacheStaleIndicator
cachedValueWeightsStamp - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
cacheIndicator - Variable in class cc.mallet.fst.ThreadedOptimizable
cacheStale - Variable in class cc.mallet.classify.MaxEntOptimizableByGE
cacheStale - Variable in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
CacheStaleIndicator - Interface in cc.mallet.fst: Indicates when the value/gradient during training becomes stale.
cacheValueAndGradient() - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByGE
CachingOptimizable - Class in cc.mallet.grmm.util: Created: Aug 27, 2004
CachingOptimizable() - Constructor for class cc.mallet.grmm.util.CachingOptimizable
CachingOptimizable.ByBatchGradient - Class in cc.mallet.grmm.util
CachingOptimizable.ByBatchGradient() - Constructor for class cc.mallet.grmm.util.CachingOptimizable.ByBatchGradient
CachingOptimizable.ByGradient - Class in cc.mallet.grmm.util
CachingOptimizable.ByGradient() - Constructor for class cc.mallet.grmm.util.CachingOptimizable.ByGradient
calcGainRatios(InstanceList, int[], int) - Static method in class cc.mallet.types.GainRatio: Calculates gain ratios for all (feature, split point) pairs snd returns array of:
calcPerLabelInfoGains(InstanceList) - Static method in class cc.mallet.types.PerLabelInfoGain
calculateNCRP(TObjectDoubleHashMap<HierarchicalLDA.NCRPNode>, HierarchicalLDA.NCRPNode, double) - Method in class cc.mallet.topics.HierarchicalLDA
calculateWordLikelihood(TObjectDoubleHashMap<HierarchicalLDA.NCRPNode>, HierarchicalLDA.NCRPNode, double, TIntIntHashMap[], double[], int, int) - Method in class cc.mallet.topics.HierarchicalLDA
callEvaluator(ACRF, InstanceList, InstanceList, InstanceList, int, ACRFEvaluator) - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer
Calo2Classify - Class in cc.mallet.classify.tui: Classify documents, run trials, print statistics from a vector file.
Calo2Classify() - Constructor for class cc.mallet.classify.tui.Calo2Classify
canIterateAllTransitions() - Method in class cc.mallet.fst.Transducer: Some transducers are "generative", meaning that you can get a sequence out of them without giving them an input sequence.
cardinality() - Method in class cc.mallet.types.FeatureSelection
cc.mallet.classify - package cc.mallet.classify: Classes for training and classifying instances.
cc.mallet.classify.constraints.ge - package cc.mallet.classify.constraints.ge
cc.mallet.classify.constraints.pr - package cc.mallet.classify.constraints.pr
cc.mallet.classify.evaluate - package cc.mallet.classify.evaluate: Classes for computing and displaying the quaility of a classification trial, including accuracy, precision, and confusion matrix.
cc.mallet.classify.examples - package cc.mallet.classify.examples: Example classes showing how to use classifiers.
cc.mallet.classify.tests - package cc.mallet.classify.tests: JUnit tests for classifiers
cc.mallet.classify.tui - package cc.mallet.classify.tui: Command line programs for document classification.
cc.mallet.cluster - package cc.mallet.cluster: Unsupervised clustering of Instance objects within an InstanceList.
cc.mallet.cluster.clustering_scorer - package cc.mallet.cluster.clustering_scorer
cc.mallet.cluster.evaluate - package cc.mallet.cluster.evaluate
cc.mallet.cluster.evaluate.tests - package cc.mallet.cluster.evaluate.tests
cc.mallet.cluster.examples - package cc.mallet.cluster.examples
cc.mallet.cluster.iterator - package cc.mallet.cluster.iterator
cc.mallet.cluster.iterator.tests - package cc.mallet.cluster.iterator.tests
cc.mallet.cluster.neighbor_evaluator - package cc.mallet.cluster.neighbor_evaluator
cc.mallet.cluster.tui - package cc.mallet.cluster.tui
cc.mallet.cluster.util - package cc.mallet.cluster.util
cc.mallet.examples - package cc.mallet.examples
cc.mallet.extract - package cc.mallet.extract: Unimplemented.
cc.mallet.extract.pipe - package cc.mallet.extract.pipe
cc.mallet.extract.test - package cc.mallet.extract.test
cc.mallet.fst - package cc.mallet.fst: Transducers, including Conditional Random Fields (CRFs).
cc.mallet.fst.confidence - package cc.mallet.fst.confidence
cc.mallet.fst.semi_supervised - package cc.mallet.fst.semi_supervised
cc.mallet.fst.semi_supervised.constraints - package cc.mallet.fst.semi_supervised.constraints
cc.mallet.fst.semi_supervised.pr - package cc.mallet.fst.semi_supervised.pr
cc.mallet.fst.semi_supervised.pr.constraints - package cc.mallet.fst.semi_supervised.pr.constraints
cc.mallet.fst.semi_supervised.tui - package cc.mallet.fst.semi_supervised.tui
cc.mallet.fst.tests - package cc.mallet.fst.tests: Tests for Transducers, including Conditional Random Fields (CRFs).
cc.mallet.grmm.examples - package cc.mallet.grmm.examples
cc.mallet.grmm.inference - package cc.mallet.grmm.inference
cc.mallet.grmm.inference.gbp - package cc.mallet.grmm.inference.gbp
cc.mallet.grmm.learning - package cc.mallet.grmm.learning
cc.mallet.grmm.learning.extract - package cc.mallet.grmm.learning.extract
cc.mallet.grmm.learning.templates - package cc.mallet.grmm.learning.templates
cc.mallet.grmm.test - package cc.mallet.grmm.test
cc.mallet.grmm.types - package cc.mallet.grmm.types
cc.mallet.grmm.util - package cc.mallet.grmm.util
cc.mallet.optimize - package cc.mallet.optimize: Classes for finding the maximum of a function.
cc.mallet.optimize.tests - package cc.mallet.optimize.tests: JUnit tests for maximize.
cc.mallet.pipe - package cc.mallet.pipe: Classes for processing arbitrary data into instances.
cc.mallet.pipe.iterator - package cc.mallet.pipe.iterator: Classes that generate instances from different kinds of input or data structures.
cc.mallet.pipe.iterator.tests - package cc.mallet.pipe.iterator.tests
cc.mallet.pipe.tests - package cc.mallet.pipe.tests: JUnit tests for pipes.
cc.mallet.pipe.tsf - package cc.mallet.pipe.tsf: TokenSequenceFeature Pipes.
cc.mallet.pipe.tsf.tests - package cc.mallet.pipe.tsf.tests: JUnit tests for TokenSequenceFeature Pipes.
cc.mallet.share.casutton.ner - package cc.mallet.share.casutton.ner
cc.mallet.share.mccallum.ner - package cc.mallet.share.mccallum.ner: Named entity recognizer.
cc.mallet.share.upenn - package cc.mallet.share.upenn: Utilities that currently include a command line wrapper for the maxent classifier.
cc.mallet.share.upenn.ner - package cc.mallet.share.upenn.ner
cc.mallet.share.weili.ner - package cc.mallet.share.weili.ner
cc.mallet.share.weili.ner.enron - package cc.mallet.share.weili.ner.enron
cc.mallet.topics - package cc.mallet.topics
cc.mallet.topics.tui - package cc.mallet.topics.tui
cc.mallet.types - package cc.mallet.types: Fundamental MALLET types, including FeatureVector, Instance, Label etc.
cc.mallet.types.tests - package cc.mallet.types.tests: JUnit tests for Fundamental MALLET types.
cc.mallet.util - package cc.mallet.util: Miscellaneous utilities including command line processing, math functions, lexing, logging.
cc.mallet.util.resources.wn - package cc.mallet.util.resources.wn
cc.mallet.util.search - package cc.mallet.util.search
cc.mallet.util.tests - package cc.mallet.util.tests: JUnit tests for the miscellaneous utilities.
CERTAIN_WEIGHT - Static variable in class cc.mallet.fst.Transducer
ChainedInstanceIterator - Class in cc.mallet.types: Deprecated.
ChainedInstanceIterator(Iterator<Instance>, ChainedInstanceIterator) - Constructor for class cc.mallet.types.ChainedInstanceIterator: Deprecated. Both source and target may be null.
changePriority(QueueElement, double) - Method in class cc.mallet.util.search.MinHeap
changePriority(QueueElement, double) - Method in interface cc.mallet.util.search.PriorityQueue: Change the priority of queue element e to priority.
CharSequence2CharNGrams - Class in cc.mallet.pipe: Transform a character sequence into a token sequence of character N grams.
CharSequence2CharNGrams(int, boolean) - Constructor for class cc.mallet.pipe.CharSequence2CharNGrams
CharSequence2TokenSequence - Class in cc.mallet.pipe: Pipe that tokenizes a character sequence.
CharSequence2TokenSequence(CharSequenceLexer) - Constructor for class cc.mallet.pipe.CharSequence2TokenSequence
CharSequence2TokenSequence(String) - Constructor for class cc.mallet.pipe.CharSequence2TokenSequence
CharSequence2TokenSequence(Pattern) - Constructor for class cc.mallet.pipe.CharSequence2TokenSequence
CharSequence2TokenSequence() - Constructor for class cc.mallet.pipe.CharSequence2TokenSequence
CharSequenceArray2TokenSequence - Class in cc.mallet.pipe: Transform an array of character Sequences into a token sequence.
CharSequenceArray2TokenSequence() - Constructor for class cc.mallet.pipe.CharSequenceArray2TokenSequence
CharSequenceLexer - Class in cc.mallet.util
CharSequenceLexer() - Constructor for class cc.mallet.util.CharSequenceLexer
CharSequenceLexer(Pattern) - Constructor for class cc.mallet.util.CharSequenceLexer
CharSequenceLexer(String) - Constructor for class cc.mallet.util.CharSequenceLexer
CharSequenceLexer(CharSequence, Pattern) - Constructor for class cc.mallet.util.CharSequenceLexer
CharSequenceLexer(CharSequence, String) - Constructor for class cc.mallet.util.CharSequenceLexer
CharSequenceLowercase - Class in cc.mallet.pipe: Replace the data string with a lowercased version.
CharSequenceLowercase() - Constructor for class cc.mallet.pipe.CharSequenceLowercase
CharSequenceRemoveHTML - Class in cc.mallet.pipe: This pipe removes HTML from a CharSequence.
CharSequenceRemoveHTML() - Constructor for class cc.mallet.pipe.CharSequenceRemoveHTML
CharSequenceRemoveUUEncodedBlocks - Class in cc.mallet.pipe
CharSequenceRemoveUUEncodedBlocks() - Constructor for class cc.mallet.pipe.CharSequenceRemoveUUEncodedBlocks
CharSequenceReplace - Class in cc.mallet.pipe: Given a string, repeatedly look for matches of the regex, and replace the entire match with the given replacement string.
CharSequenceReplace(Pattern, String) - Constructor for class cc.mallet.pipe.CharSequenceReplace
CharSubsequence - Class in cc.mallet.pipe: Given a string, return only the portion of the string inside a regex parenthesized group.
CharSubsequence(Pattern, int) - Constructor for class cc.mallet.pipe.CharSubsequence
CharSubsequence(Pattern) - Constructor for class cc.mallet.pipe.CharSubsequence
check(ArrayList<GEConstraint>, double[][], double[][][], FeatureVectorSequence) - Method in class cc.mallet.fst.semi_supervised.GELattice: Verifies the correctness of the lattice computations.
checkBreakeven(double) - Method in class cc.mallet.types.Dirichlet
checkWithinRange(double, double, double) - Static method in class cc.mallet.util.Maths: Checks if min <= value <= max.
cholesky(double[], int) - Static method in class cc.mallet.util.MVNormal: Simple Cholesky decomposition, with no checks on squareness, symmetricality, or positive definiteness.
Classification - Class in cc.mallet.classify: The result of classifying a single instance.
Classification(Instance, Classifier, Labeling) - Constructor for class cc.mallet.classify.Classification
Classification2ConfidencePredictingFeatureVector - Class in cc.mallet.pipe: Pipe features from underlying classifier to the confidence prediction instance list
Classification2ConfidencePredictingFeatureVector() - Constructor for class cc.mallet.pipe.Classification2ConfidencePredictingFeatureVector
Classifier - Class in cc.mallet.classify: Abstract parent of all Classifiers.
Classifier() - Constructor for class cc.mallet.classify.Classifier: For serialization only.
Classifier(Pipe) - Constructor for class cc.mallet.classify.Classifier
classifier - Variable in class cc.mallet.classify.MaxEntOptimizableByGE
Classifier2Info - Class in cc.mallet.classify.tui: Diagnostic facilities for a classifier.
Classifier2Info() - Constructor for class cc.mallet.classify.tui.Classifier2Info
ClassifierAccuracyEvaluator - Class in cc.mallet.classify
ClassifierAccuracyEvaluator(InstanceList[], String[]) - Constructor for class cc.mallet.classify.ClassifierAccuracyEvaluator
ClassifierAccuracyEvaluator(InstanceList, String) - Constructor for class cc.mallet.classify.ClassifierAccuracyEvaluator
ClassifierAccuracyEvaluator(InstanceList, String, InstanceList, String) - Constructor for class cc.mallet.classify.ClassifierAccuracyEvaluator
ClassifierAccuracyEvaluator(InstanceList, String, InstanceList, String, InstanceList, String) - Constructor for class cc.mallet.classify.ClassifierAccuracyEvaluator
ClassifierEnsemble - Class in cc.mallet.classify: Classifer for an ensemble of classifers, combined with learned weights.
ClassifierEnsemble(Classifier[], double[]) - Constructor for class cc.mallet.classify.ClassifierEnsemble
ClassifierEnsembleTrainer - Class in cc.mallet.classify
ClassifierEnsembleTrainer(Classifier[]) - Constructor for class cc.mallet.classify.ClassifierEnsembleTrainer
ClassifierEvaluator - Class in cc.mallet.classify
ClassifierEvaluator(InstanceList[], String[]) - Constructor for class cc.mallet.classify.ClassifierEvaluator
ClassifierEvaluator(InstanceList, String) - Constructor for class cc.mallet.classify.ClassifierEvaluator
ClassifierEvaluator(InstanceList, String, InstanceList, String) - Constructor for class cc.mallet.classify.ClassifierEvaluator
ClassifierEvaluator(InstanceList, String, InstanceList, String, InstanceList, String) - Constructor for class cc.mallet.classify.ClassifierEvaluator
ClassifierTrainer<C extends Classifier> - Class in cc.mallet.classify: Each ClassifierTrainer trains one Classifier based on various interfaces for consuming training data.
ClassifierTrainer() - Constructor for class cc.mallet.classify.ClassifierTrainer
ClassifierTrainer.ByActiveLearning<C extends Classifier> - Interface in cc.mallet.classify: For active learning, in which this trainer will select certain instances and request that the Labeler instance label them.
ClassifierTrainer.ByIncrements<C extends Classifier> - Interface in cc.mallet.classify: For various kinds of online learning by batches, where training instances are presented, consumed for learning immediately.
ClassifierTrainer.ByInstanceIncrements<C extends Classifier> - Interface in cc.mallet.classify: For online learning that can operate on one instance at a time.
ClassifierTrainer.ByOptimization<C extends Classifier> - Interface in cc.mallet.classify
ClassifierTrainer.Factory<CT extends ClassifierTrainer<? extends Classifier>> - Class in cc.mallet.classify: Instances of a Factory know how to create new ClassifierTrainers to apply to new Classifiers.
ClassifierTrainer.Factory() - Constructor for class cc.mallet.classify.ClassifierTrainer.Factory
classify(Instance) - Method in class cc.mallet.classify.AdaBoost
classify(Instance, int) - Method in class cc.mallet.classify.AdaBoost: Classify the given instance using only the first numWeakClassifiersToUse classifiers trained during boosting
classify(Instance) - Method in class cc.mallet.classify.AdaBoostM2
classify(Instance, int) - Method in class cc.mallet.classify.AdaBoostM2: Classify the given instance using only the first numWeakClassifiersToUse classifiers trained during boosting
classify(Instance) - Method in class cc.mallet.classify.BaggingClassifier
classify(Instance) - Method in class cc.mallet.classify.BalancedWinnow: Classifies an instance using BalancedWinnow's weights
classify(Instance) - Method in class cc.mallet.classify.C45
classify(InstanceList) - Method in class cc.mallet.classify.Classifier
classify(Instance[]) - Method in class cc.mallet.classify.Classifier
classify(Instance) - Method in class cc.mallet.classify.Classifier
classify(Object) - Method in class cc.mallet.classify.Classifier: Pipe the object through this classifier's pipe, then classify the resulting instance.
classify(Instance) - Method in class cc.mallet.classify.ClassifierEnsemble
classify(Instance) - Method in class cc.mallet.classify.ConfidencePredictingClassifier
classify(Instance) - Method in class cc.mallet.classify.DecisionTree
classify(Instance) - Method in class cc.mallet.classify.MaxEnt
classify(Instance) - Method in class cc.mallet.classify.MCMaxEnt
classify(Instance) - Method in class cc.mallet.classify.NaiveBayes: Classify an instance using NaiveBayes according to the trained data.
classify(Instance) - Method in class cc.mallet.classify.PRAuxClassifier
classify(Instance) - Method in class cc.mallet.classify.RankMaxEnt
classify(Instance) - Method in class cc.mallet.classify.Winnow: Classifies an instance using Winnow's weights
classify(Instance) - Method in class cc.mallet.pipe.AddClassifierTokenPredictions.TokenClassifiers
classify(Instance, boolean) - Method in class cc.mallet.pipe.AddClassifierTokenPredictions.TokenClassifiers
classify(Classifier, String[]) - Static method in class cc.mallet.share.upenn.MaxEntShell: Compute the maxent classification of an instance.
classify(Classifier, String[][]) - Static method in class cc.mallet.share.upenn.MaxEntShell: Compute the maxent classifications of an array of instances
classify(Classifier, Iterator<Instance>) - Static method in class cc.mallet.share.upenn.MaxEntShell: Compute the maxent classifications for unlabeled instances given by an iterator.
ClassifyingNeighborEvaluator - Class in cc.mallet.cluster.neighbor_evaluator: A NeighborEvaluator that is backed by a Classifier.
ClassifyingNeighborEvaluator(Classifier, String) - Constructor for class cc.mallet.cluster.neighbor_evaluator.ClassifyingNeighborEvaluator
classShortName(Object) - Static method in class cc.mallet.grmm.util.GeneralUtils
cleanFields(FieldCleaner) - Method in class cc.mallet.extract.Extraction
cleanFieldValue(String) - Method in interface cc.mallet.extract.FieldCleaner: Returns a post-processed version of a field.
cleanFieldValue(String) - Method in class cc.mallet.extract.RegexFieldCleaner
clear() - Method in class cc.mallet.grmm.types.BitVarSet
clear() - Method in class cc.mallet.grmm.types.FactorGraph: Removes all potentias from this model.
clear() - Method in class cc.mallet.grmm.types.HashVarSet
clear() - Method in class cc.mallet.grmm.types.ListVarSet
clear() - Method in class cc.mallet.grmm.types.UnmodifiableVarSet
clear() - Method in class cc.mallet.grmm.util.CSIntInt2ObjectMultiMap
clear() - Method in class cc.mallet.types.CrossValidationIterator: Calls clear on each fold.
clear() - Method in class cc.mallet.types.InstanceList
clear() - Method in class cc.mallet.types.MultiInstanceList
clear() - Method in class cc.mallet.types.PagedInstanceList
clearSource() - Method in class cc.mallet.types.Instance
clone() - Method in class cc.mallet.grmm.inference.TRP
clone() - Method in class cc.mallet.grmm.inference.TRP.ConvergenceTerminator
clone() - Method in class cc.mallet.grmm.inference.TRP.DefaultConvergenceTerminator
clone() - Method in class cc.mallet.grmm.inference.TRP.IterationTerminator
clone() - Method in interface cc.mallet.grmm.inference.TRP.TerminationCondition
clone() - Method in class cc.mallet.grmm.types.AbstractTableFactor
clone() - Method in class cc.mallet.grmm.types.HashVarSet
clone() - Method in class cc.mallet.types.Alphabet
clone() - Method in class cc.mallet.types.FeatureSelection
clone() - Method in class cc.mallet.types.Instance
clone() - Method in class cc.mallet.types.InstanceList
clone() - Method in class cc.mallet.types.Matrixn
clone() - Method in class cc.mallet.types.MultiInstanceList
clone() - Method in class cc.mallet.types.Multinomial.Estimator
clone() - Method in class cc.mallet.types.SparseMatrixn
clone() - Method in class cc.mallet.util.DoubleList
cloneDoubleList() - Method in class cc.mallet.util.DoubleList
cloneEmpty() - Method in class cc.mallet.types.InstanceList
cloneEmpty() - Method in class cc.mallet.types.MultiInstanceList
cloneEmpty() - Method in class cc.mallet.types.PagedInstanceList
cloneEmptyInto(InstanceList) - Method in class cc.mallet.types.InstanceList
cloneEmptyInto(InstanceList) - Method in class cc.mallet.types.MultiInstanceList
cloneMatrix() - Method in class cc.mallet.types.AugmentableFeatureVector
cloneMatrix() - Method in interface cc.mallet.types.ConstantMatrix
cloneMatrix() - Method in class cc.mallet.types.DenseMatrix
cloneMatrix() - Method in class cc.mallet.types.DenseVector
cloneMatrix() - Method in class cc.mallet.types.FeatureVector
cloneMatrix() - Method in class cc.mallet.types.HashedSparseVector
cloneMatrix() - Method in class cc.mallet.types.IndexedSparseVector
cloneMatrix() - Method in class cc.mallet.types.Matrix2: Deprecated.
cloneMatrix() - Method in class cc.mallet.types.Matrixn
cloneMatrix() - Method in class cc.mallet.types.SparseMatrixn
cloneMatrix() - Method in class cc.mallet.types.SparseVector: CLONING
cloneMatrix2() - Method in class cc.mallet.types.Matrix2: Deprecated.
cloneMatrixZeroed() - Method in class cc.mallet.types.AugmentableFeatureVector
cloneMatrixZeroed() - Method in class cc.mallet.types.FeatureVector
cloneMatrixZeroed() - Method in class cc.mallet.types.HashedSparseVector
cloneMatrixZeroed() - Method in class cc.mallet.types.IndexedSparseVector
cloneMatrixZeroed() - Method in class cc.mallet.types.SparseVector
cloneViaSerialization(Serializable) - Static method in class cc.mallet.types.tests.TestSerializable: Clones a given object by serializing it to a byte array and reading it back.
cluster(InstanceList) - Method in class cc.mallet.cluster.Clusterer: Return a clustering of an InstanceList
cluster(InstanceList) - Method in class cc.mallet.cluster.HillClimbingClusterer: While not converged, calls improveClustering to modify the current predicted Clustering.
cluster(InstanceList, int, Clustering) - Method in class cc.mallet.cluster.HillClimbingClusterer: While not converged, call improveClustering to modify the current predicted Clustering.
cluster(InstanceList) - Method in class cc.mallet.cluster.KMeans: Cluster instances
Clusterer - Class in cc.mallet.cluster: An abstract class for clustering a set of points.
Clusterer(Pipe) - Constructor for class cc.mallet.cluster.Clusterer: Creates a new Clusterer instance.
Clustering - Class in cc.mallet.cluster
Clustering(InstanceList, int, int[]) - Constructor for class cc.mallet.cluster.Clustering: Clustering constructor.
clustering - Variable in class cc.mallet.cluster.iterator.NeighborIterator
ClusteringEvaluator - Class in cc.mallet.cluster.evaluate: Evaluates a predicted Clustering against a true Clustering.
ClusteringEvaluator() - Constructor for class cc.mallet.cluster.evaluate.ClusteringEvaluator
ClusteringEvaluators - Class in cc.mallet.cluster.evaluate: A list of ClusteringEvaluators.
ClusteringEvaluators(ClusteringEvaluator[]) - Constructor for class cc.mallet.cluster.evaluate.ClusteringEvaluators
Clusterings - Class in cc.mallet.cluster
Clusterings(Clustering[]) - Constructor for class cc.mallet.cluster.Clusterings
Clusterings2Clusterer - Class in cc.mallet.cluster.tui
Clusterings2Clusterer() - Constructor for class cc.mallet.cluster.tui.Clusterings2Clusterer
Clusterings2Clusterer.ClusteringPipe - Class in cc.mallet.cluster.tui
Clusterings2Clusterer.ClusteringPipe(int[], int[], int[]) - Constructor for class cc.mallet.cluster.tui.Clusterings2Clusterer.ClusteringPipe
Clusterings2Clusterings - Class in cc.mallet.cluster.tui
Clusterings2Clusterings() - Constructor for class cc.mallet.cluster.tui.Clusterings2Clusterings
Clusterings2Info - Class in cc.mallet.cluster.tui
Clusterings2Info() - Constructor for class cc.mallet.cluster.tui.Clusterings2Info
ClusteringScorer - Interface in cc.mallet.cluster.clustering_scorer: Assign a score to a Clustering.
clusterKBest(InstanceList, int) - Method in class cc.mallet.cluster.HillClimbingClusterer
clusterKBest(InstanceList, int, Clustering, int) - Method in class cc.mallet.cluster.HillClimbingClusterer: Return the K most recent solutions.
clusterKBest(InstanceList, int) - Method in class cc.mallet.cluster.KBestClusterer
clusterPotentials() - Method in class cc.mallet.grmm.inference.JunctionTree: Returns a collection of all the potentials of cliques in the junction tree.
ClusterSampleIterator - Class in cc.mallet.cluster.iterator: Sample clusters of Instances.
ClusterSampleIterator(Clustering, Randoms, double, int) - Constructor for class cc.mallet.cluster.iterator.ClusterSampleIterator
ClusterUtils - Class in cc.mallet.cluster.util: Utility functions for Clusterings.
ClusterUtils() - Constructor for class cc.mallet.cluster.util.ClusterUtils
ClusterVariationalRegionGenerator - Class in cc.mallet.grmm.inference.gbp: Created: Jun 1, 2005
ClusterVariationalRegionGenerator() - Constructor for class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator
ClusterVariationalRegionGenerator(ClusterVariationalRegionGenerator.BaseRegionComputer) - Constructor for class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator
ClusterVariationalRegionGenerator.BaseRegionComputer - Interface in cc.mallet.grmm.inference.gbp
ClusterVariationalRegionGenerator.ByFactorRegionComputer - Class in cc.mallet.grmm.inference.gbp: Region computer where each top-level region consists of a single factor node.
ClusterVariationalRegionGenerator.ByFactorRegionComputer() - Constructor for class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator.ByFactorRegionComputer
ClusterVariationalRegionGenerator.Grid2x2RegionComputer - Class in cc.mallet.grmm.inference.gbp
ClusterVariationalRegionGenerator.Grid2x2RegionComputer() - Constructor for class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator.Grid2x2RegionComputer
collectAlphaStatistics() - Method in class cc.mallet.topics.WorkerRunnable
collectConstraints(InstanceList) - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF
collectConstraints(InstanceList) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable
collectConstraints(InstanceList) - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable
collectConstraints(InstanceList) - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable
collectDocumentStatistics() - Method in class cc.mallet.topics.TopicModelDiagnostics
CollectionUtils - Class in cc.mallet.util: * Created: Sun Jan 25 01:04:29 2004
CollectionUtils.Fn - Interface in cc.mallet.util
color(int) - Method in class cc.mallet.classify.evaluate.Graph.Legend
ColorUtils - Class in cc.mallet.util: Utilities for dealing with RGB-style colors.
ColorUtils() - Constructor for class cc.mallet.util.ColorUtils
columnPlusEquals(int, double) - Method in class cc.mallet.types.DenseVector
columnPlusEquals(int, double) - Method in class cc.mallet.types.HashedSparseVector
columnPlusEquals(int, double) - Method in class cc.mallet.types.IndexedSparseVector
columnPlusEquals(int, Vector, double) - Method in class cc.mallet.types.Matrix2: Deprecated.
columnPlusEquals(int, double, double) - Method in class cc.mallet.types.Matrix2: Deprecated.
combine(double[]) - Method in class cc.mallet.cluster.neighbor_evaluator.MedoidEvaluator.Average
combine(double[]) - Method in interface cc.mallet.cluster.neighbor_evaluator.MedoidEvaluator.CombiningStrategy
combine(double[]) - Method in class cc.mallet.cluster.neighbor_evaluator.MedoidEvaluator.Maximum
combine(double[]) - Method in class cc.mallet.cluster.neighbor_evaluator.MedoidEvaluator.Minimum
combine(double[]) - Method in class cc.mallet.cluster.neighbor_evaluator.PairwiseEvaluator.Average
combine(double[]) - Method in interface cc.mallet.cluster.neighbor_evaluator.PairwiseEvaluator.CombiningStrategy
combine(double[]) - Method in class cc.mallet.cluster.neighbor_evaluator.PairwiseEvaluator.Maximum
combine(double[]) - Method in class cc.mallet.cluster.neighbor_evaluator.PairwiseEvaluator.Minimum
combineGradients(Collection<double[]>, double[]) - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood: Adds gradients from all batches.
combineGradients(Collection<double[]>, double[]) - Method in interface cc.mallet.optimize.Optimizable.ByCombiningBatchGradient
combineLists(InstanceList, InstanceList) - Static method in class cc.mallet.cluster.util.ClusterUtils
CommandOption - Class in cc.mallet.util
CommandOption(Class, String, String, Class, boolean, String, String) - Constructor for class cc.mallet.util.CommandOption
CommandOption(Class, String, String, Class, boolean, String) - Constructor for class cc.mallet.util.CommandOption: Deprecated.
CommandOption.Boolean - Class in cc.mallet.util
CommandOption.Boolean(Class, String, String, boolean, boolean, String, String) - Constructor for class cc.mallet.util.CommandOption.Boolean
CommandOption.Double - Class in cc.mallet.util
CommandOption.Double(Class, String, String, boolean, double, String, String) - Constructor for class cc.mallet.util.CommandOption.Double
CommandOption.DoubleArray - Class in cc.mallet.util
CommandOption.DoubleArray(Class, String, String, boolean, double[], String, String) - Constructor for class cc.mallet.util.CommandOption.DoubleArray
CommandOption.File - Class in cc.mallet.util
CommandOption.File(Class, String, String, boolean, File, String, String) - Constructor for class cc.mallet.util.CommandOption.File
CommandOption.Integer - Class in cc.mallet.util
CommandOption.Integer(Class, String, String, boolean, int, String, String) - Constructor for class cc.mallet.util.CommandOption.Integer
CommandOption.IntegerArray - Class in cc.mallet.util
CommandOption.IntegerArray(Class, String, String, boolean, int[], String, String) - Constructor for class cc.mallet.util.CommandOption.IntegerArray
CommandOption.List - Class in cc.mallet.util
CommandOption.List(String, CommandOption[]) - Constructor for class cc.mallet.util.CommandOption.List
CommandOption.ListProviding - Interface in cc.mallet.util: For objects that can provide CommandOption.List's (which can be merged into other lists.
CommandOption.Object - Class in cc.mallet.util
CommandOption.Object(Class, String, String, boolean, Object, String, String) - Constructor for class cc.mallet.util.CommandOption.Object
CommandOption.ObjectFromBean - Class in cc.mallet.util
CommandOption.ObjectFromBean(Class, String, String, boolean, Object, String, String) - Constructor for class cc.mallet.util.CommandOption.ObjectFromBean
CommandOption.Set - Class in cc.mallet.util
CommandOption.Set(Class, String, String, boolean, String[], int, String, String) - Constructor for class cc.mallet.util.CommandOption.Set
CommandOption.SpacedStrings - Class in cc.mallet.util
CommandOption.SpacedStrings(Class, String, String, boolean, String[], String, String) - Constructor for class cc.mallet.util.CommandOption.SpacedStrings
CommandOption.String - Class in cc.mallet.util
CommandOption.String(Class, String, String, boolean, String, String, String) - Constructor for class cc.mallet.util.CommandOption.String
commonPrefix(String[]) - Static method in class cc.mallet.util.Strings
commonPrefixIndex(String[]) - Static method in class cc.mallet.util.Strings
compact() - Method in class cc.mallet.grmm.inference.JunctionTree
compare(Object, Object) - Method in class cc.mallet.classify.evaluate.AccuracyCoverage.ClassificationComparator
compare(double, int, int, int) - Static method in class cc.mallet.types.Dirichlet
compare(double) - Method in class cc.mallet.util.Univariate
compareTo(Object) - Method in class cc.mallet.fst.confidence.InstanceWithConfidence
compareTo(Object) - Method in class cc.mallet.fst.confidence.PipedInstanceWithConfidence
compareTo(Object) - Method in class cc.mallet.fst.Segment
compareTo(Object) - Method in class cc.mallet.grmm.types.Variable
compareTo(Object) - Method in class cc.mallet.types.IDSorter
compareTo(Object) - Method in class cc.mallet.types.Label
completionCost() - Method in class cc.mallet.util.search.AStarNode: Get the completion cost for the underlying state.
completionCost() - Method in interface cc.mallet.util.search.AStarState: Get the cost to completion.
computeAssignment(Assignment, VarSet) - Method in class cc.mallet.grmm.learning.ACRF.Template
computeBaseRegions(FactorGraph) - Method in interface cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator.BaseRegionComputer: Returns a list of top-level regions for use in the cluster variational method.
computeBaseRegions(FactorGraph) - Method in class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator.ByFactorRegionComputer
computeBaseRegions(FactorGraph) - Method in class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator.Grid2x2RegionComputer
computeBatchGradient(double[], int, int[]) - Method in class cc.mallet.grmm.util.CachingOptimizable.ByBatchGradient
computeBatchValue(int, int[]) - Method in class cc.mallet.grmm.util.CachingOptimizable.ByBatchGradient
computeBin(FeatureVector) - Method in interface cc.mallet.grmm.learning.templates.SimilarTokensTemplate.FeatureVectorBinner
computeBin(FeatureVector) - Method in class cc.mallet.grmm.learning.templates.SimilarTokensTemplate.WordFeatureBinner
computeCostAndPrune() - Method in class cc.mallet.classify.C45.Node
computeCurrentResids() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph
computeExpectations(FeatureVector, double[], double) - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints
computeExpectations(FeatureVector, double[], double) - Method in interface cc.mallet.classify.constraints.ge.MaxEntGEConstraint: Compute expectations using provided distribution over labels.
computeExpectations(FeatureVector, double[], double) - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints
computeExpectations(ArrayList<SumLattice>) - Method in interface cc.mallet.fst.semi_supervised.constraints.GEConstraint: Compute expectations using cached lattices.
computeExpectations(ArrayList<SumLattice>) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints
computeExpectations(ArrayList<SumLattice>) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints
computeExpectations(ArrayList<SumLattice>) - Method in class cc.mallet.fst.semi_supervised.constraints.SelfTransitionGEConstraint
computeExpectations(ArrayList<SumLattice>) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints
computeExpectations() - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization: Resets, computes and fills expectations from all instances, also updating the entropy value.
computeFactor(ACRF.UnrolledVarSet) - Method in class cc.mallet.grmm.learning.ACRF.FixedFactorTemplate
computeFactor(ACRF.UnrolledVarSet) - Method in class cc.mallet.grmm.learning.ACRF.Template
computeLogLikelihood() - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.AbstractInferencer
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.BruteForceInferencer
computeMarginals(JunctionTree) - Method in class cc.mallet.grmm.inference.BruteForceInferencer
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.gbp.ParentChildGBP
computeMarginals(FactorGraph) - Method in interface cc.mallet.grmm.inference.Inferencer: Computes marginal distributions for a factor graph.
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.JunctionTreeInferencer
computeMarginals(JunctionTree) - Method in class cc.mallet.grmm.inference.JunctionTreeInferencer
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.LoopyBP
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.ResidualBP
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.SamplingInferencer
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.TreeBP
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.TRP
computeMarginals(FactorGraph) - Method in class cc.mallet.grmm.inference.VariableElimination
computeNormalizationFactor(FactorGraph) - Method in class cc.mallet.grmm.inference.VariableElimination: Computes the normalization constant for a model.
computeSizes(Factor) - Static method in class cc.mallet.grmm.types.Factors
computeTestResults(InstanceList, List) - Static method in class cc.mallet.grmm.learning.DefaultAcrfTrainer.LogEvaluator
computeValue() - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable
computeValue() - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable
computeValue() - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable
computeValue() - Method in class cc.mallet.grmm.util.CachingOptimizable.ByGradient
computeValueAndGradient(int) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable
computeValueGradient(double[]) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable: Computes the gradient of the penalized log likelihood of the ACRF, and places it in cachedGradient[].
computeValueGradient(double[]) - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable: Computes the gradient of the penalized log likelihood of the ACRF, and places it in cachedGradient[].
computeValueGradient(double[]) - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable: Computes the gradient of the penalized log likelihood of the ACRF, and places it in cachedGradient[].
computeValueGradient(double[]) - Method in class cc.mallet.grmm.util.CachingOptimizable.ByGradient
computeVars(Factor) - Static method in class cc.mallet.grmm.types.Factors
ConcatenatedInstanceIterator - Class in cc.mallet.pipe.iterator
ConcatenatedInstanceIterator(Iterator<Instance>[]) - Constructor for class cc.mallet.pipe.iterator.ConcatenatedInstanceIterator
concatenatePipes(Pipe, Pipe) - Static method in class cc.mallet.pipe.PipeUtils
CONDITION_WW - Static variable in class cc.mallet.grmm.learning.PwplACRFTrainer
confidence() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator.EntityConfidence
ConfidenceCorrectorEvaluator - Class in cc.mallet.fst.confidence: Calculates the effectiveness of "constrained viterbi" in propagating corrections in one segment of a sequence to other segments.
ConfidenceCorrectorEvaluator(Object[], Object[]) - Constructor for class cc.mallet.fst.confidence.ConfidenceCorrectorEvaluator
ConfidenceEvaluator - Class in cc.mallet.fst.confidence
ConfidenceEvaluator(Vector, int) - Constructor for class cc.mallet.fst.confidence.ConfidenceEvaluator
ConfidenceEvaluator(Vector) - Constructor for class cc.mallet.fst.confidence.ConfidenceEvaluator
ConfidenceEvaluator(Segment[], boolean) - Constructor for class cc.mallet.fst.confidence.ConfidenceEvaluator
ConfidenceEvaluator(InstanceWithConfidence[], boolean) - Constructor for class cc.mallet.fst.confidence.ConfidenceEvaluator
ConfidenceEvaluator(PipedInstanceWithConfidence[], boolean) - Constructor for class cc.mallet.fst.confidence.ConfidenceEvaluator
ConfidenceEvaluator.EntityConfidence - Class in cc.mallet.fst.confidence: a simple class to store a confidence score and whether or not this labeling is correct
ConfidenceEvaluator.EntityConfidence(double, boolean, String) - Constructor for class cc.mallet.fst.confidence.ConfidenceEvaluator.EntityConfidence
ConfidenceEvaluator.EntityConfidence(double, boolean, Sequence, int, int) - Constructor for class cc.mallet.fst.confidence.ConfidenceEvaluator.EntityConfidence
ConfidencePredictingClassifier - Class in cc.mallet.classify
ConfidencePredictingClassifier(Classifier, Classifier) - Constructor for class cc.mallet.classify.ConfidencePredictingClassifier
ConfidencePredictingClassifierTrainer - Class in cc.mallet.classify
ConfidencePredictingClassifierTrainer(ClassifierTrainer, InstanceList, Pipe) - Constructor for class cc.mallet.classify.ConfidencePredictingClassifierTrainer
ConfidencePredictingClassifierTrainer(ClassifierTrainer, InstanceList) - Constructor for class cc.mallet.classify.ConfidencePredictingClassifierTrainer
ConfidenceTokenizationFilter - Class in cc.mallet.extract: Created: Oct 26, 2005
ConfidenceTokenizationFilter(ExtractionConfidenceEstimator, TokenizationFilter) - Constructor for class cc.mallet.extract.ConfidenceTokenizationFilter
confusion - Variable in class cc.mallet.grmm.learning.DefaultAcrfTrainer.TestResults
ConfusionMatrix - Class in cc.mallet.classify.evaluate: Calculates and prints confusion matrix, accuracy, and precision for a given clasification trial.
ConfusionMatrix(Trial) - Constructor for class cc.mallet.classify.evaluate.ConfusionMatrix: Constructs matrix and calculates values
ConjugateGradient - Class in cc.mallet.optimize
ConjugateGradient(Optimizable.ByGradientValue, double) - Constructor for class cc.mallet.optimize.ConjugateGradient
ConjugateGradient(Optimizable.ByGradientValue) - Constructor for class cc.mallet.optimize.ConjugateGradient
ConllNer2003Sentence2TokenSequence - Class in cc.mallet.share.casutton.ner: Reads a data file in CoNLL 2003 format, and makes some simple transformations.
ConllNer2003Sentence2TokenSequence() - Constructor for class cc.mallet.share.casutton.ner.ConllNer2003Sentence2TokenSequence
ConllNer2003Sentence2TokenSequence(boolean, boolean) - Constructor for class cc.mallet.share.casutton.ner.ConllNer2003Sentence2TokenSequence
ConllNer2003Sentence2TokenSequence - Class in cc.mallet.share.mccallum.ner
ConllNer2003Sentence2TokenSequence() - Constructor for class cc.mallet.share.mccallum.ner.ConllNer2003Sentence2TokenSequence
ConllNer2003Sentence2TokenSequence(boolean) - Constructor for class cc.mallet.share.mccallum.ner.ConllNer2003Sentence2TokenSequence
constant(int[], double) - Static method in class cc.mallet.grmm.util.Matrices
ConstantFactor - Class in cc.mallet.grmm.types: $Id: ConstantFactor.java,v 1.1 2007/10/22 21:37:44 mccallum Exp $
ConstantFactor(double) - Constructor for class cc.mallet.grmm.types.ConstantFactor
ConstantMatrix - Interface in cc.mallet.types
ConstrainedForwardBackwardConfidenceEstimator - Class in cc.mallet.fst.confidence: Estimates the confidence of a Segment extracted by a Transducer by performing a "constrained lattice" calculation.
ConstrainedForwardBackwardConfidenceEstimator(Transducer) - Constructor for class cc.mallet.fst.confidence.ConstrainedForwardBackwardConfidenceEstimator
ConstrainedViterbiTransducerCorrector - Class in cc.mallet.fst.confidence: Corrects a subset of the Segments produced by a Transducer.
ConstrainedViterbiTransducerCorrector(TransducerConfidenceEstimator, Transducer) - Constructor for class cc.mallet.fst.confidence.ConstrainedViterbiTransducerCorrector
ConstrainedViterbiTransducerCorrector(Transducer) - Constructor for class cc.mallet.fst.confidence.ConstrainedViterbiTransducerCorrector
constraintIndices - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints
constraints - Variable in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints
constraints - Variable in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints
constraints - Variable in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints
constraints - Variable in class cc.mallet.classify.MaxEntGERangeTrainer
constraints - Variable in class cc.mallet.classify.MaxEntGETrainer
constraints - Variable in class cc.mallet.classify.MaxEntOptimizableByGE
constraints - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
constraints - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood
constraints - Variable in class cc.mallet.fst.CRFTrainerByStochasticGradient
constraints - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints
constraints - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints
constraints - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints
constraints - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints
constraints - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
constraintsFile - Static variable in class cc.mallet.classify.tui.Vectors2FeatureConstraints
constraintsList - Variable in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints
constraintsMap - Variable in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints
ConstraintsOptimizableByPR - Class in cc.mallet.fst.semi_supervised.pr: Optimizable for E-step/I-projection in Posterior Regularization (PR).
ConstraintsOptimizableByPR(CRF, InstanceList, PRAuxiliaryModel) - Constructor for class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
ConstraintsOptimizableByPR(CRF, InstanceList, PRAuxiliaryModel, int) - Constructor for class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) - Method in class cc.mallet.extract.BIOTokenizationFilter
constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) - Method in class cc.mallet.extract.ConfidenceTokenizationFilter
constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) - Method in class cc.mallet.extract.DefaultTokenizationFilter
constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) - Method in class cc.mallet.extract.HierarchicalTokenizationFilter
constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) - Method in interface cc.mallet.extract.TokenizationFilter: Converts a the sequence of labels into a set of labeled spans.
constructRegionGraph(FactorGraph) - Method in class cc.mallet.grmm.inference.gbp.BPRegionGenerator
constructRegionGraph(FactorGraph) - Method in class cc.mallet.grmm.inference.gbp.ClusterVariationalRegionGenerator
constructRegionGraph(FactorGraph) - Method in class cc.mallet.grmm.inference.gbp.Kikuchi4SquareRegionGenerator
constructRegionGraph(FactorGraph) - Method in interface cc.mallet.grmm.inference.gbp.RegionGraphGenerator: Construct a region graph from an artbitrary model.
contains(Object) - Method in class cc.mallet.grmm.types.BidirectionalIntObjectMap
contains(Object) - Method in class cc.mallet.grmm.types.BitVarSet
contains(Object) - Method in class cc.mallet.grmm.types.HashVarSet
contains(Object) - Method in class cc.mallet.grmm.types.ListVarSet
contains(Object) - Method in class cc.mallet.grmm.types.UnmodifiableVarSet
contains(Object) - Method in class cc.mallet.types.Alphabet
contains(Object) - Method in class cc.mallet.types.FeatureSelection
contains(int) - Method in class cc.mallet.types.FeatureSelection
contains(Object) - Method in class cc.mallet.types.FeatureVector
contains(Object) - Method in class cc.mallet.types.MultiInstanceList
contains(QueueElement) - Method in class cc.mallet.util.search.MinHeap
contains(QueueElement) - Method in interface cc.mallet.util.search.PriorityQueue: Does the queue contain an element?
containsAll(Collection) - Method in class cc.mallet.grmm.types.BitVarSet
containsAll(BitVarSet) - Method in class cc.mallet.grmm.types.BitVarSet: Efficient version of containsAll() for BitSetCliques.
containsAll(Collection) - Method in class cc.mallet.grmm.types.HashVarSet
containsAll(Collection) - Method in class cc.mallet.grmm.types.UnmodifiableVarSet
containsObject(Object) - Method in class cc.mallet.grmm.types.Tree
containsVar(Variable) - Method in class cc.mallet.grmm.types.AbstractFactor
containsVar(Variable) - Method in class cc.mallet.grmm.types.AbstractTableFactor: Returns true iff this potential is over the given variable
containsVar(Variable) - Method in class cc.mallet.grmm.types.Assignment: Returns true if this assignment specifies a value for var
containsVar(Variable) - Method in class cc.mallet.grmm.types.CPT
containsVar(Variable) - Method in interface cc.mallet.grmm.types.Factor: Returns whether the potential is over the given variable.
containsVar(Variable) - Method in class cc.mallet.grmm.types.FactorGraph: Returns whether this variable is part of the model.
contentsAsCharSequence(Reader) - Static method in class cc.mallet.util.IoUtils
contentsAsString(File) - Static method in class cc.mallet.util.IoUtils
CONTINUOUS - Static variable in class cc.mallet.grmm.types.Variable: Number of outcomes for a continous variable.
continuousVarsOf(Factor) - Static method in class cc.mallet.grmm.types.Factors
converged - Variable in class cc.mallet.cluster.GreedyAgglomerative: True if should stop clustering.
converged(Clustering) - Method in class cc.mallet.cluster.GreedyAgglomerative
converged(Clustering) - Method in class cc.mallet.cluster.GreedyAgglomerativeByDensity
converged(Clustering) - Method in class cc.mallet.cluster.HillClimbingClusterer
converged - Variable in class cc.mallet.fst.CRFTrainerByStochasticGradient
convert(InstanceList, Noop) - Static method in class cc.mallet.pipe.AddClassifierTokenPredictions: Converts each instance containing a FeatureVectorSequence to multiple instances, each containing an AugmentableFeatureVector as data.
convert(Instance, Noop) - Static method in class cc.mallet.pipe.AddClassifierTokenPredictions
copy() - Method in interface cc.mallet.fst.semi_supervised.constraints.GEConstraint: This is used in multi-threading.
copy() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelKLGEConstraints
copy() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2GEConstraints
copy() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints
copy() - Method in class cc.mallet.fst.semi_supervised.constraints.SelfTransitionGEConstraint
copy() - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelKLGEConstraints
copy() - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelL2GEConstraints
copy() - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints
copy() - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint
copy() - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints
copy() - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints.OneLabelPRConstraint
copy() - Method in interface cc.mallet.fst.semi_supervised.pr.constraints.PRConstraint: This is used in multi-threading.
copy() - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel
copyAndMergeClusters(Clustering, int, int) - Static method in class cc.mallet.cluster.util.ClusterUtils
copyAndMergeInstances(Clustering, int, int) - Static method in class cc.mallet.cluster.util.ClusterUtils
copyAndMergeInstances(Clustering, int[]) - Static method in class cc.mallet.cluster.util.ClusterUtils
copyOldMessages() - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation
copyWithNewLabels(Clustering) - Static method in class cc.mallet.cluster.util.ClusterUtils
corr(Factor) - Static method in class cc.mallet.grmm.types.Factors
corr(Univariate, Univariate) - Static method in class cc.mallet.util.StatFunctions
correct() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator.EntityConfidence
correct() - Method in class cc.mallet.fst.confidence.InstanceWithConfidence
correct() - Method in class cc.mallet.fst.confidence.PipedInstanceWithConfidence
correct() - Method in class cc.mallet.fst.Segment
correctLeastConfidentSegments(InstanceList, Object[], Object[]) - Method in class cc.mallet.fst.confidence.ConstrainedViterbiTransducerCorrector
correctLeastConfidentSegments(InstanceList, Object[], Object[], boolean) - Method in class cc.mallet.fst.confidence.ConstrainedViterbiTransducerCorrector: Returns an ArrayList of corrected Sequences.
correctLeastConfidentSegments(InstanceList, Object[], Object[]) - Method in class cc.mallet.fst.confidence.IsolatedSegmentTransducerCorrector
correctLeastConfidentSegments(InstanceList, Object[], Object[]) - Method in interface cc.mallet.fst.confidence.TransducerCorrector
correctT - Variable in class cc.mallet.grmm.learning.DefaultAcrfTrainer.TestResults
correlation() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator: Calculate pearson's R for the corellation between confidence and correct, where 1 = correct and -1 = incorrect
cosh(double) - Static method in class cc.mallet.util.Maths
cost() - Method in class cc.mallet.util.search.SearchNode.NextNodeIterator: The cost associated to the transition from the previous state to this state.
cost() - Method in class cc.mallet.util.search.SearchState.NextStateIterator: The cost of the transition to the current state.
count - Variable in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints.MaxEntFLGEConstraint
count - Variable in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints.MaxEntL2IndGEConstraint
count - Variable in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints.MaxEntFLPRConstraint
count - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints.OneLabelGEConstraint
count - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints.OneLabelL2IndGEConstraint
count - Variable in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints.TwoLabelGEConstraint
count - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint
count - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints.OneLabelPRConstraint
count(int[], int) - Static method in class cc.mallet.util.ArrayUtils: Returns the number of times a value occurs in a given array.
count() - Method in class cc.mallet.util.FeatureCounter
count(String, char) - Static method in class cc.mallet.util.Strings
CountMatches - Class in cc.mallet.pipe.tsf
CountMatches(String, Pattern, int) - Constructor for class cc.mallet.pipe.tsf.CountMatches
CountMatches(String, Pattern) - Constructor for class cc.mallet.pipe.tsf.CountMatches
CountMatchesAlignedWithOffsets - Class in cc.mallet.pipe.tsf
CountMatchesAlignedWithOffsets(String, Pattern, int[], boolean) - Constructor for class cc.mallet.pipe.tsf.CountMatchesAlignedWithOffsets
CountMatchesAlignedWithOffsets(String, Pattern, int[]) - Constructor for class cc.mallet.pipe.tsf.CountMatchesAlignedWithOffsets
CountMatchesMatching - Class in cc.mallet.pipe.tsf
CountMatchesMatching(String, Pattern, Pattern, boolean) - Constructor for class cc.mallet.pipe.tsf.CountMatchesMatching
CountMatchesMatching(String, Pattern, Pattern) - Constructor for class cc.mallet.pipe.tsf.CountMatchesMatching
cov(Univariate, Univariate) - Static method in class cc.mallet.util.StatFunctions
CPT - Class in cc.mallet.grmm.types: $Id: CPT.java,v 1.1 2007/10/22 21:37:44 mccallum Exp $
CPT(DiscreteFactor, Variable) - Constructor for class cc.mallet.grmm.types.CPT
createAccuracyArray() - Method in class cc.mallet.classify.evaluate.AccuracyCoverage: Creates array of accuracy values for coverage at each step as defined by numBuckets.
createArrayList(Object[]) - Static method in class cc.mallet.util.ArrayListUtils
createBlankSubset(Variable[]) - Method in class cc.mallet.grmm.types.AbstractTableFactor
createBlankSubset(Variable[]) - Method in class cc.mallet.grmm.types.LogTableFactor
createBlankSubset(Variable[]) - Method in class cc.mallet.grmm.types.TableFactor
createBoltzmannMachine(double[][], double[]) - Static method in class cc.mallet.grmm.types.UndirectedModel: Creates an undirected model that corresponds to a Boltzmann machine with the given weights and biases.
createEvaluator(String) - Static method in class cc.mallet.grmm.learning.extract.AcrfExtractorTui
createEvaluator(String) - Static method in class cc.mallet.grmm.learning.GenericAcrfTui
createFactorMatrix(ACRF.UnrolledVarSet) - Method in class cc.mallet.grmm.learning.ACRF.Template: Creates an empty matrix for use in storing factor values when this template is unrolled.
createForMaxProduct() - Static method in class cc.mallet.grmm.inference.JunctionTreeInferencer
createForMaxProduct() - Static method in class cc.mallet.grmm.inference.LoopyBP
createForMaxProduct() - Static method in class cc.mallet.grmm.inference.ResidualBP
createForMaxProduct() - Static method in class cc.mallet.grmm.inference.TreeBP
createForMaxProduct() - Static method in class cc.mallet.grmm.inference.TRP
createFromRegex(Alphabet, Pattern) - Static method in class cc.mallet.types.FeatureSelection: Creates a FeatureSelection that includes only those features whose names match a given regex.
createGainRatio(InstanceList) - Static method in class cc.mallet.types.GainRatio: Constructs a GainRatio object.
createGainRatio(InstanceList, int[], int) - Static method in class cc.mallet.types.GainRatio: Constructs a GainRatio object
createGrid(RandomGraphs.FactorGenerator, int) - Static method in class cc.mallet.grmm.inference.RandomGraphs
createGridWithObs(RandomGraphs.FactorGenerator, RandomGraphs.FactorGenerator, int) - Static method in class cc.mallet.grmm.inference.RandomGraphs
createOptimizable(ACRF, InstanceList) - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer
createOptimizable(ACRF, InstanceList) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer
createOptimizable(ACRF, InstanceList) - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer
createOptimizable(ACRF, InstanceList) - Method in class cc.mallet.grmm.learning.PwplACRFTrainer
createPipe() - Method in class cc.mallet.pipe.tests.TestInstancePipe
createRandomChain(Randoms, int) - Static method in class cc.mallet.grmm.inference.RandomGraphs
createRandomClustering(InstanceList, Randoms) - Static method in class cc.mallet.cluster.util.ClusterUtils
createRandomGrid(int, int, int, Random) - Static method in class cc.mallet.grmm.test.TestInference
createReverseTransitionMatrices(CRF) - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByGE: Initializes data structures for mapping between a destination state and its source states / transition indices.
createSingletonClustering(InstanceList) - Static method in class cc.mallet.cluster.util.ClusterUtils: Initializes Clustering to one Instance per cluster.
createSpan(Tokenization, int, int) - Method in class cc.mallet.extract.BIOTokenizationFilter
createSpan(Tokenization, int, int) - Method in class cc.mallet.extract.BIOTokenizationFilterWithTokenIndices
createTasks() - Method in class cc.mallet.fst.ThreadedOptimizable: Creates tasks to be executed in parallel, each task looks at a batch of data.
createTestModels() - Static method in class cc.mallet.grmm.test.TestInference
createUniformChain(int) - Static method in class cc.mallet.grmm.inference.RandomGraphs
createUniformGrid(int) - Static method in class cc.mallet.grmm.inference.RandomGraphs
CRF - Class in cc.mallet.fst: Represents a CRF model.
CRF(Pipe, Pipe) - Constructor for class cc.mallet.fst.CRF
CRF(Alphabet, Alphabet) - Constructor for class cc.mallet.fst.CRF
CRF(CRF) - Constructor for class cc.mallet.fst.CRF: Create a CRF whose states and weights are a copy of those from another CRF.
crf - Variable in class cc.mallet.fst.CRFCacheStaleIndicator
crf - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
crf - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood
crf - Variable in class cc.mallet.fst.CRFTrainerByStochasticGradient
crf - Variable in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization
crf - Variable in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR
crf - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
CRF.Factors - Class in cc.mallet.fst: A simple, transparent container to hold the parameters or sufficient statistics for the CRF.
CRF.Factors() - Constructor for class cc.mallet.fst.CRF.Factors: Construct a new empty Factors with a new empty weightsAlphabet, 0-length initialWeights and finalWeights, and the other arrays null.
CRF.Factors(CRF.Factors) - Constructor for class cc.mallet.fst.CRF.Factors: Construct new Factors by mimicking the structure of the other one, but with zero values.
CRF.Factors(CRF.Factors, boolean) - Constructor for class cc.mallet.fst.CRF.Factors: Construct new Factors by copying the other one.
CRF.Factors(CRF) - Constructor for class cc.mallet.fst.CRF.Factors: Construct a new Factors with the same structure as the parameters of 'crf', but with values initialized to zero.
CRF.Factors.Incrementor - Class in cc.mallet.fst: Instances of this inner class can be passed to various inference methods, which can then gather/increment sufficient statistics counts into the containing Factor instance.
CRF.Factors.Incrementor() - Constructor for class cc.mallet.fst.CRF.Factors.Incrementor
CRF.Factors.WeightedIncrementor - Class in cc.mallet.fst
CRF.Factors.WeightedIncrementor(double) - Constructor for class cc.mallet.fst.CRF.Factors.WeightedIncrementor
CRF.State - Class in cc.mallet.fst
CRF.State() - Constructor for class cc.mallet.fst.CRF.State
CRF.State(String, int, double, double, String[], String[], String[][], CRF) - Constructor for class cc.mallet.fst.CRF.State
CRF.TransitionIterator - Class in cc.mallet.fst
CRF.TransitionIterator(CRF.State, FeatureVectorSequence, int, String, CRF) - Constructor for class cc.mallet.fst.CRF.TransitionIterator
CRF.TransitionIterator(CRF.State, FeatureVector, String, CRF) - Constructor for class cc.mallet.fst.CRF.TransitionIterator
CRFCacheStaleIndicator - Class in cc.mallet.fst: Indicates when the value/gradient becomes stale based on updates to CRF's parameters.
CRFCacheStaleIndicator(CRF) - Constructor for class cc.mallet.fst.CRFCacheStaleIndicator
CRFExtractor - Class in cc.mallet.extract: Created: Oct 12, 2004
CRFExtractor(CRF) - Constructor for class cc.mallet.extract.CRFExtractor
CRFExtractor(File) - Constructor for class cc.mallet.extract.CRFExtractor
CRFExtractor(CRF, Pipe) - Constructor for class cc.mallet.extract.CRFExtractor
CRFExtractor(CRF, Pipe, TokenizationFilter) - Constructor for class cc.mallet.extract.CRFExtractor
CRFExtractor(CRF, Pipe, TokenizationFilter, String) - Constructor for class cc.mallet.extract.CRFExtractor
CRFOptimizableByBatchLabelLikelihood - Class in cc.mallet.fst: Implements label likelihood gradient computations for batches of data, can be easily parallelized.
CRFOptimizableByBatchLabelLikelihood(CRF, InstanceList, int) - Constructor for class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
CRFOptimizableByBatchLabelLikelihood.Factory - Class in cc.mallet.fst
CRFOptimizableByBatchLabelLikelihood.Factory() - Constructor for class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood.Factory
CRFOptimizableByEntropyRegularization - Class in cc.mallet.fst.semi_supervised: A CRF objective function that is the entropy of the CRF's predictions on unlabeled data.
CRFOptimizableByEntropyRegularization(CRF, InstanceList, double) - Constructor for class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization: Initializes the structures.
CRFOptimizableByEntropyRegularization(CRF, InstanceList) - Constructor for class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization: Initializes the structures (sets the scaling factor to 1.0).
CRFOptimizableByGE - Class in cc.mallet.fst.semi_supervised: Optimizable for CRF using Generalized Expectation constraints that consider either a single label or a pair of labels of a linear chain CRF.
CRFOptimizableByGE(CRF, ArrayList<GEConstraint>, InstanceList, StateLabelMap, int) - Constructor for class cc.mallet.fst.semi_supervised.CRFOptimizableByGE
CRFOptimizableByGE(CRF, ArrayList<GEConstraint>, InstanceList, StateLabelMap, int, double) - Constructor for class cc.mallet.fst.semi_supervised.CRFOptimizableByGE
CRFOptimizableByGradientValues - Class in cc.mallet.fst: A CRF objective function that is the sum of multiple objective functions that implement Optimizable.ByGradientValue.
CRFOptimizableByGradientValues(CRF, Optimizable.ByGradientValue[]) - Constructor for class cc.mallet.fst.CRFOptimizableByGradientValues
CRFOptimizableByKL - Class in cc.mallet.fst.semi_supervised.pr: M-step/M-projection for PR.
CRFOptimizableByKL(CRF, InstanceList, PRAuxiliaryModel, double[][][][], int, double) - Constructor for class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL
CRFOptimizableByLabelLikelihood - Class in cc.mallet.fst: An objective function for CRFs that is the label likelihood plus a Gaussian or hyperbolic prior on parameters.
CRFOptimizableByLabelLikelihood(CRF, InstanceList) - Constructor for class cc.mallet.fst.CRFOptimizableByLabelLikelihood
CRFOptimizableByLabelLikelihood.Factory - Class in cc.mallet.fst
CRFOptimizableByLabelLikelihood.Factory() - Constructor for class cc.mallet.fst.CRFOptimizableByLabelLikelihood.Factory
CRFTrainerByEntropyRegularization - Class in cc.mallet.fst.semi_supervised: A CRF trainer that maximizes the log-likelihood plus a weighted entropy regularization term on unlabeled data.
CRFTrainerByEntropyRegularization(CRF) - Constructor for class cc.mallet.fst.semi_supervised.CRFTrainerByEntropyRegularization
CRFTrainerByGE - Class in cc.mallet.fst.semi_supervised: Trains a CRF using Generalized Expectation constraints that consider either a single label or a pair of labels of a linear chain CRF.
CRFTrainerByGE(CRF, ArrayList<GEConstraint>) - Constructor for class cc.mallet.fst.semi_supervised.CRFTrainerByGE
CRFTrainerByGE(CRF, ArrayList<GEConstraint>, int) - Constructor for class cc.mallet.fst.semi_supervised.CRFTrainerByGE
CRFTrainerByL1LabelLikelihood - Class in cc.mallet.fst: CRF trainer that implements L1-regularization.
CRFTrainerByL1LabelLikelihood(CRF) - Constructor for class cc.mallet.fst.CRFTrainerByL1LabelLikelihood
CRFTrainerByL1LabelLikelihood(CRF, double) - Constructor for class cc.mallet.fst.CRFTrainerByL1LabelLikelihood: Constructor for CRF trainer.
CRFTrainerByLabelLikelihood - Class in cc.mallet.fst: Unlike ClassifierTrainer, TransducerTrainer is not "stateless" between calls to train.
CRFTrainerByLabelLikelihood(CRF) - Constructor for class cc.mallet.fst.CRFTrainerByLabelLikelihood
CRFTrainerByLikelihoodAndGE - Class in cc.mallet.fst.semi_supervised
CRFTrainerByLikelihoodAndGE(CRF, ArrayList<GEConstraint>, StateLabelMap) - Constructor for class cc.mallet.fst.semi_supervised.CRFTrainerByLikelihoodAndGE
CRFTrainerByPR - Class in cc.mallet.fst.semi_supervised.pr: Posterior regularization trainer.
CRFTrainerByPR(CRF, ArrayList<PRConstraint>) - Constructor for class cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR
CRFTrainerByPR(CRF, ArrayList<PRConstraint>, int) - Constructor for class cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR
CRFTrainerByStochasticGradient - Class in cc.mallet.fst: Trains CRF by stochastic gradient.
CRFTrainerByStochasticGradient(CRF, InstanceList) - Constructor for class cc.mallet.fst.CRFTrainerByStochasticGradient
CRFTrainerByStochasticGradient(CRF, double) - Constructor for class cc.mallet.fst.CRFTrainerByStochasticGradient
CRFTrainerByThreadedLabelLikelihood - Class in cc.mallet.fst
CRFTrainerByThreadedLabelLikelihood(CRF, int) - Constructor for class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood
CRFTrainerByValueGradients - Class in cc.mallet.fst: A CRF trainer that can combine multiple objective functions, each represented by a Optmizable.ByValueGradient.
CRFTrainerByValueGradients(CRF, Optimizable.ByGradientValue[]) - Constructor for class cc.mallet.fst.CRFTrainerByValueGradients
CRFTrainerByValueGradients.OptimizableCRF - Class in cc.mallet.fst: An optimizable CRF that contains a collection of objective functions.
CRFTrainerByValueGradients.OptimizableCRF(CRF, InstanceList) - Constructor for class cc.mallet.fst.CRFTrainerByValueGradients.OptimizableCRF
CRFWriter - Class in cc.mallet.fst: Saves a trained model to specified filename.
CRFWriter(String) - Constructor for class cc.mallet.fst.CRFWriter
CrossTemplate1 - Class in cc.mallet.grmm.examples: $Id: CrossTemplate1.java,v 1.1 2007/10/22 21:38:02 mccallum Exp $
CrossTemplate1(int, int) - Constructor for class cc.mallet.grmm.examples.CrossTemplate1
CrossValidationIterator - Class in cc.mallet.types: An iterator which splits an InstanceList into n-folds and iterates over the folds for use in n-fold cross-validation.
CrossValidationIterator(InstanceList, int, Random) - Constructor for class cc.mallet.types.CrossValidationIterator: Constructs a new n-fold cross-validation iterator
CrossValidationIterator(InstanceList, int) - Constructor for class cc.mallet.types.CrossValidationIterator: Constructs a new n-fold cross-validation iterator
crossValidationIterator(int, int) - Method in class cc.mallet.types.InstanceList
crossValidationIterator(int) - Method in class cc.mallet.types.InstanceList
crossValidationIterator(int, int) - Method in class cc.mallet.types.MultiInstanceList
crossValidationIterator(int) - Method in class cc.mallet.types.MultiInstanceList
CSIntInt2ObjectMultiMap - Class in cc.mallet.grmm.util: A map that maps (int, int) --> object, where each (int,int) key is allowed to map to multiple objects.
CSIntInt2ObjectMultiMap() - Constructor for class cc.mallet.grmm.util.CSIntInt2ObjectMultiMap
Csv2Array - Class in cc.mallet.pipe: Converts a string of comma separated values to an array.
Csv2Array() - Constructor for class cc.mallet.pipe.Csv2Array
Csv2Array(String) - Constructor for class cc.mallet.pipe.Csv2Array
Csv2Array(CharSequenceLexer) - Constructor for class cc.mallet.pipe.Csv2Array
Csv2Classify - Class in cc.mallet.classify.tui: Command line tool for classifying a sequence of instances directly from text input, without creating an instance list.
Csv2Classify() - Constructor for class cc.mallet.classify.tui.Csv2Classify
Csv2FeatureVector - Class in cc.mallet.pipe: Converts a string of the form feature_1:val_1 feature_2:val_2 ...
Csv2FeatureVector(int) - Constructor for class cc.mallet.pipe.Csv2FeatureVector
Csv2FeatureVector() - Constructor for class cc.mallet.pipe.Csv2FeatureVector
Csv2Vectors - Class in cc.mallet.classify.tui: Command line import tool for loading a sequence of instances from a single file, with one instance per line of the input file.
Csv2Vectors() - Constructor for class cc.mallet.classify.tui.Csv2Vectors
CsvIterator - Class in cc.mallet.pipe.iterator: This iterator, perhaps more properly called a Line Pattern Iterator, reads through a file and returns one instance per line, based on a regular expression.
CsvIterator(Reader, Pattern, int, int, int) - Constructor for class cc.mallet.pipe.iterator.CsvIterator
CsvIterator(Reader, String, int, int, int) - Constructor for class cc.mallet.pipe.iterator.CsvIterator
CsvIterator(String, String, int, int, int) - Constructor for class cc.mallet.pipe.iterator.CsvIterator
cumulativeAccuracy() - Method in class cc.mallet.classify.evaluate.AccuracyCoverage: Finds the "area under the acc/cov curve" steps by one percentage point and calcs area of trapezoid
currentMessage() - Method in class cc.mallet.grmm.inference.MessageArray.ToMsgsIterator
currentToIdx() - Method in class cc.mallet.grmm.inference.MessageArray.ToMsgsIterator
curry(int) - Method in class cc.mallet.grmm.util.MIntInt2ObjectMap: Returns an iterator over the set of (key2, value) pairs that match (key1).

D data - Variable in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization data - Static variable in class cc.mallet.fst.tests.TestCRF data - Static variable in class cc.mallet.fst.tests.TestMEMM data - Variable in class cc.mallet.topics.LDAHyper Deprecated. data - Variable in class cc.mallet.topics.NPTopicModel data - Variable in class cc.mallet.topics.ParallelTopicModel data - Variable in class cc.mallet.topics.PolylingualTopicModel data - Variable in class cc.mallet.topics.SimpleLDA data - Variable in class cc.mallet.types.Instance dataLogLikelihood(InstanceList) - Method in class cc.mallet.classify.NaiveBayes DecisionTree - Class in cc.mallet.classify Decision Tree classifier. DecisionTree(Pipe, DecisionTree.Node) - Constructor for class cc.mallet.classify.DecisionTree DecisionTree.Node - Class in cc.mallet.classify DecisionTree.Node(InstanceList, DecisionTree.Node, FeatureSelection) - Constructor for class cc.mallet.classify.DecisionTree.Node DecisionTreeTrainer - Class in cc.mallet.classify A decision tree learner, roughly ID3, but only to a fixed given depth in all branches. DecisionTreeTrainer(int) - Constructor for class cc.mallet.classify.DecisionTreeTrainer DecisionTreeTrainer() - Constructor for class cc.mallet.classify.DecisionTreeTrainer DecisionTreeTrainer.Factory - Class in cc.mallet.classify DecisionTreeTrainer.Factory() - Constructor for class cc.mallet.classify.DecisionTreeTrainer.Factory decompact() - Method in class cc.mallet.grmm.inference.JunctionTree deepClone() - Method in class cc.mallet.pipe.SimpleTokenizer deepCopy(MIntInt2ObjectMap) - Method in class cc.mallet.grmm.inference.MessageArray DEFAULT - Static variable in class cc.mallet.grmm.types.Universe DEFAULT_BETA - Static variable in class cc.mallet.topics.LDAHyper Deprecated. DEFAULT_BETA - Static variable in class cc.mallet.topics.NPTopicModel DEFAULT_BETA - Static variable in class cc.mallet.topics.ParallelTopicModel DEFAULT_BETA - Static variable in class cc.mallet.topics.PolylingualTopicModel DEFAULT_BETA - Static variable in class cc.mallet.topics.SimpleLDA DEFAULT_BETA - Static variable in class cc.mallet.topics.WorkerRunnable DEFAULT_COOLING_RATE - Static variable in class cc.mallet.classify.BalancedWinnowTrainer 0.5 DEFAULT_DELTA - Static variable in class cc.mallet.classify.BalancedWinnowTrainer 0.1 DEFAULT_DOC_PROPORTIONS - Static variable in class cc.mallet.topics.TopicModelDiagnostics DEFAULT_EPSILON - Static variable in class cc.mallet.classify.BalancedWinnowTrainer 0.5 DEFAULT_MAX_DEPTH - Static variable in class cc.mallet.classify.DecisionTreeTrainer DEFAULT_MAX_ITER - Static variable in class cc.mallet.grmm.inference.LoopyBP DEFAULT_MAX_ITER - Static variable in class cc.mallet.grmm.inference.ResidualBP DEFAULT_MAX_ITERATIONS - Static variable in class cc.mallet.classify.BalancedWinnowTrainer 30 DEFAULT_MAX_RESETS - Static variable in class cc.mallet.fst.CRFTrainerByValueGradients DEFAULT_MIN_INFO_GAIN_SPLIT - Static variable in class cc.mallet.classify.DecisionTreeTrainer DefaultAcrfTrainer - Class in cc.mallet.grmm.learning Class for training ACRFs. DefaultAcrfTrainer() - Constructor for class cc.mallet.grmm.learning.DefaultAcrfTrainer DefaultAcrfTrainer.FileEvaluator - Class in cc.mallet.grmm.learning DefaultAcrfTrainer.FileEvaluator(File) - Constructor for class cc.mallet.grmm.learning.DefaultAcrfTrainer.FileEvaluator DefaultAcrfTrainer.LogEvaluator - Class in cc.mallet.grmm.learning DefaultAcrfTrainer.LogEvaluator() - Constructor for class cc.mallet.grmm.learning.DefaultAcrfTrainer.LogEvaluator DefaultAcrfTrainer.TestResults - Class in cc.mallet.grmm.learning defaultFeatureIndex - Variable in class cc.mallet.classify.MaxEnt defaultFeatureIndex - Variable in class cc.mallet.classify.MaxEntOptimizableByGE defaultIntersection(VarSet, VarSet) - Static method in class cc.mallet.grmm.inference.Utils DefaultTokenizationFilter - Class in cc.mallet.extract Created: Nov 12, 2004 DefaultTokenizationFilter() - Constructor for class cc.mallet.extract.DefaultTokenizationFilter defaultValue - Variable in class cc.mallet.util.CommandOption.Boolean defaultValue - Variable in class cc.mallet.util.CommandOption.Double defaultValue - Variable in class cc.mallet.util.CommandOption.DoubleArray defaultValue - Variable in class cc.mallet.util.CommandOption.File defaultValue - Variable in class cc.mallet.util.CommandOption.Integer defaultValue - Variable in class cc.mallet.util.CommandOption.IntegerArray defaultValue - Variable in class cc.mallet.util.CommandOption.Object defaultValue - Variable in class cc.mallet.util.CommandOption.Set defaultValue - Variable in class cc.mallet.util.CommandOption.SpacedStrings defaultValue - Variable in class cc.mallet.util.CommandOption.String defaultValueToString() - Method in class cc.mallet.util.CommandOption.Boolean defaultValueToString() - Method in class cc.mallet.util.CommandOption defaultValueToString() - Method in class cc.mallet.util.CommandOption.Double defaultValueToString() - Method in class cc.mallet.util.CommandOption.DoubleArray defaultValueToString() - Method in class cc.mallet.util.CommandOption.File defaultValueToString() - Method in class cc.mallet.util.CommandOption.Integer defaultValueToString() - Method in class cc.mallet.util.CommandOption.IntegerArray defaultValueToString() - Method in class cc.mallet.util.CommandOption.Object defaultValueToString() - Method in class cc.mallet.util.CommandOption.ObjectFromBean defaultValueToString() - Method in class cc.mallet.util.CommandOption.Set defaultValueToString() - Method in class cc.mallet.util.CommandOption.SpacedStrings defaultValueToString() - Method in class cc.mallet.util.CommandOption.String defaultWeights - Variable in class cc.mallet.fst.CRF.Factors deletionMark - Static variable in class cc.mallet.types.FeatureSequenceWithBigrams delogify() - Method in class cc.mallet.grmm.types.AbstractFactor DenseMatrix - Class in cc.mallet.types DenseMatrix() - Constructor for class cc.mallet.types.DenseMatrix DenseVector - Class in cc.mallet.types DenseVector(double[], boolean) - Constructor for class cc.mallet.types.DenseVector DenseVector(double[]) - Constructor for class cc.mallet.types.DenseVector DenseVector(int) - Constructor for class cc.mallet.types.DenseVector depth() - Method in class cc.mallet.classify.C45.Node The root has depth zero. depth() - Method in class cc.mallet.classify.DecisionTree.Node The root has depth zero. describeTransition(double) - Method in class cc.mallet.fst.CRF.TransitionIterator describeTransition(double) - Method in class cc.mallet.fst.MEMM.TransitionIterator describeTransition(double) - Method in class cc.mallet.fst.Transducer.TransitionIterator diag(int[], double) - Static method in class cc.mallet.grmm.util.Matrices diagonalToString(double[], int) - Static method in class cc.mallet.util.MVNormal digamma(double) - Static method in class cc.mallet.types.Dirichlet Calculate digamma using an asymptotic expansion involving Bernoulli numbers. DIGAMMA_COEF_1 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_10 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_2 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_3 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_4 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_5 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_6 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_7 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_8 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_COEF_9 - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_LARGE - Static variable in class cc.mallet.types.Dirichlet DIGAMMA_SMALL - Static variable in class cc.mallet.types.Dirichlet digammaDifference(double, int) - Static method in class cc.mallet.types.Dirichlet DirectedModel - Class in cc.mallet.grmm.types Class for directed graphical models. DirectedModel() - Constructor for class cc.mallet.grmm.types.DirectedModel DirectedModel(Variable[]) - Constructor for class cc.mallet.grmm.types.DirectedModel DirectedModel(int) - Constructor for class cc.mallet.grmm.types.DirectedModel Directory2FileIterator - Class in cc.mallet.pipe Convert a File object representing a directory into a FileIterator which iterates over files in the directory matching a pattern and which extracts a label from each file path to become the target field of the instance. Directory2FileIterator(FileFilter, Pattern) - Constructor for class cc.mallet.pipe.Directory2FileIterator Directory2FileIterator(Pattern, Pattern, Pattern) - Constructor for class cc.mallet.pipe.Directory2FileIterator Directory2FileIterator(String) - Constructor for class cc.mallet.pipe.Directory2FileIterator Directory2FileIterator() - Constructor for class cc.mallet.pipe.Directory2FileIterator DirectoryFilter - Class in cc.mallet.util DirectoryFilter() - Constructor for class cc.mallet.util.DirectoryFilter Dirichlet - Class in cc.mallet.types Various useful functions related to Dirichlet distributions. Dirichlet(double, double[]) - Constructor for class cc.mallet.types.Dirichlet A dirichlet parameterized by a distribution and a magnitude Dirichlet(double[]) - Constructor for class cc.mallet.types.Dirichlet A dirichlet parameterized with a single vector of positive reals Dirichlet(double[], Alphabet) - Constructor for class cc.mallet.types.Dirichlet Constructor that takes an alphabet representing the meaning of each dimension Dirichlet(Alphabet) - Constructor for class cc.mallet.types.Dirichlet A symmetric Dirichlet with alpha_i = 1.0 and the number of dimensions of the given alphabet. Dirichlet(Alphabet, double) - Constructor for class cc.mallet.types.Dirichlet A symmetric Dirichlet with alpha_i = alpha and the number of dimensions of the given alphabet. Dirichlet(int) - Constructor for class cc.mallet.types.Dirichlet A symmetric Dirichlet with alpha_i = 1.0 and size dimensions Dirichlet(int, double) - Constructor for class cc.mallet.types.Dirichlet A symmetric dirichlet: E(X_i) = E(X_j) for all i, j Dirichlet.Estimator - Class in cc.mallet.types Dirichlet.Estimator() - Constructor for class cc.mallet.types.Dirichlet.Estimator Dirichlet.Estimator(Collection<Multinomial>) - Constructor for class cc.mallet.types.Dirichlet.Estimator Dirichlet.MethodOfMomentsEstimator - Class in cc.mallet.types Dirichlet.MethodOfMomentsEstimator() - Constructor for class cc.mallet.types.Dirichlet.MethodOfMomentsEstimator dirichletMultinomialLikelihoodRatio(TIntIntHashMap, TIntIntHashMap, double, double) - Static method in class cc.mallet.types.Dirichlet What is the probability that these two observations were drawn from the same multinomial with symmetric Dirichlet prior alpha, relative to the probability that they were drawn from different multinomials both drawn from this Dirichlet? dirichletMultinomialLikelihoodRatio(int[], int[], double, double) - Static method in class cc.mallet.types.Dirichlet What is the probability that these two observations were drawn from the same multinomial with symmetric Dirichlet prior alpha, relative to the probability that they were drawn from different multinomials both drawn from this Dirichlet? dirichletMultinomialLikelihoodRatio(int[], int[]) - Method in class cc.mallet.types.Dirichlet This version uses a non-symmetric Dirichlet prior disableDoubleBuffering(Component) - Static method in class cc.mallet.util.PrintUtilities The speed and quality of printing suffers dramatically if any of the containers have double buffering turned on. disabledtestAddOrderNStates() - Method in class cc.mallet.fst.tests.TestMEMM disabledtestCost(int) - Method in class cc.mallet.fst.tests.TestMEMM disabledtestDenseSerialization() - Method in class cc.mallet.fst.tests.TestMEMM disabledtestDenseTrain() - Method in class cc.mallet.fst.tests.TestMEMM disabledtestPrint() - Method in class cc.mallet.fst.tests.TestMEMM disabledtestSerialization() - Method in class cc.mallet.fst.tests.TestMEMM disabledtestTrain() - Method in class cc.mallet.fst.tests.TestMEMM disabledtestValueGradient() - Method in class cc.mallet.fst.tests.TestMEMM DiscreteFactor - Interface in cc.mallet.grmm.types $Id: DiscreteFactor.java,v 1.1 2007/10/22 21:37:44 mccallum Exp $ discreteVarsOf(Factor) - Static method in class cc.mallet.grmm.types.Factors displayGraph() - Method in class cc.mallet.classify.evaluate.AccuracyCoverage Displays the accuracy v. displayTopWords(int, boolean) - Method in class cc.mallet.topics.ParallelTopicModel distance(SparseVector, int, SparseVector, int) - Method in interface cc.mallet.types.CachedMetric distance(SparseVector, SparseVector) - Method in interface cc.mallet.types.Metric distance(SparseVector, SparseVector) - Method in class cc.mallet.types.Minkowski Gives the Minkowski distance between two vectors. distance(SparseVector, SparseVector) - Method in class cc.mallet.types.NormalizedDotProductMetric distance(SparseVector, int, SparseVector, int) - Method in class cc.mallet.types.NormalizedDotProductMetric distLinf(AbstractTableFactor, AbstractTableFactor) - Static method in class cc.mallet.grmm.types.Factors distributionToString(double, double[]) - Static method in class cc.mallet.types.Dirichlet Create a printable list of alpha_i parameters distValueLinf(AbstractTableFactor, AbstractTableFactor) - Static method in class cc.mallet.grmm.types.Factors div() - Static method in class cc.mallet.grmm.util.Flops divideBy(Factor) - Method in class cc.mallet.grmm.types.AbstractFactor divideBy(Factor) - Method in class cc.mallet.grmm.types.AbstractTableFactor Does the conceptual equivalent of this /= pot. divideBy(double) - Method in class cc.mallet.grmm.types.AbstractTableFactor divideBy(Factor) - Method in class cc.mallet.grmm.types.BetaFactor divideBy(Factor) - Method in class cc.mallet.grmm.types.CPT divideBy(Factor) - Method in interface cc.mallet.grmm.types.Factor Computes this /= pot divideBy(Factor) - Method in class cc.mallet.grmm.types.FactorGraph divideBy(Factor) - Method in class cc.mallet.grmm.types.NormalFactor divideBy(Factor) - Method in class cc.mallet.grmm.types.UniformFactor divideBy(Factor) - Method in class cc.mallet.grmm.types.UniNormalFactor divideByInternal(DiscreteFactor) - Method in class cc.mallet.grmm.types.AbstractTableFactor divideByInternal(DiscreteFactor) - Method in class cc.mallet.grmm.types.LogTableFactor divideByInternal(DiscreteFactor) - Method in class cc.mallet.grmm.types.TableFactor divideEquals(double) - Method in class cc.mallet.types.DenseMatrix divideEquals(double) - Method in interface cc.mallet.types.Matrix divideEquals(double) - Method in class cc.mallet.types.SparseMatrixn DMRLoader - Class in cc.mallet.topics.tui This class loads data into the format for the MALLET Dirichlet-multinomial regression (DMR). DMRLoader() - Constructor for class cc.mallet.topics.tui.DMRLoader DMROptimizable - Class in cc.mallet.topics DMROptimizable() - Constructor for class cc.mallet.topics.DMROptimizable DMROptimizable(InstanceList, MaxEnt) - Constructor for class cc.mallet.topics.DMROptimizable DMRTopicModel - Class in cc.mallet.topics DMRTopicModel(int) - Constructor for class cc.mallet.topics.DMRTopicModel docLengthCounts - Variable in class cc.mallet.topics.LDAHyper Deprecated. docLengthCounts - Variable in class cc.mallet.topics.ParallelTopicModel docLengthCounts - Variable in class cc.mallet.topics.PolylingualTopicModel docLengthCounts - Variable in class cc.mallet.topics.WorkerRunnable docsPerTopic - Variable in class cc.mallet.topics.NPTopicModel DocumentClassifier - Class in cc.mallet.classify.examples DocumentClassifier() - Constructor for class cc.mallet.classify.examples.DocumentClassifier DocumentExtraction - Class in cc.mallet.extract Created: Oct 12, 2004 DocumentExtraction(String, LabelAlphabet, Tokenization, Sequence, String) - Constructor for class cc.mallet.extract.DocumentExtraction DocumentExtraction(String, LabelAlphabet, Tokenization, Sequence, Sequence, String) - Constructor for class cc.mallet.extract.DocumentExtraction DocumentExtraction(String, LabelAlphabet, Tokenization, Sequence, Sequence, String, TokenizationFilter) - Constructor for class cc.mallet.extract.DocumentExtraction DocumentExtraction(String, LabelAlphabet, Tokenization, LabeledSpans, LabeledSpans, String) - Constructor for class cc.mallet.extract.DocumentExtraction DocumentLengths - Class in cc.mallet.util DocumentLengths() - Constructor for class cc.mallet.util.DocumentLengths DocumentViewer - Class in cc.mallet.extract Diagnosis class that outputs HTML pages that allows you to view errors on a more global per-instance basis. DocumentViewer() - Constructor for class cc.mallet.extract.DocumentViewer doneWithGraph(FactorGraph) - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation doProcessOptions(Class, String[]) - Static method in class cc.mallet.grmm.learning.extract.AcrfExtractorTui doProcessOptions(Class, String[]) - Static method in class cc.mallet.grmm.learning.GenericAcrfTui dot(double[], double[]) - Static method in class cc.mallet.types.MatrixOps Deprecated. Use dotProduct() dotCache - Variable in class cc.mallet.fst.semi_supervised.GELattice doTestCost(boolean) - Method in class cc.mallet.fst.tests.TestCRF doTestSpacePrediction(boolean) - Method in class cc.mallet.fst.tests.TestCRF doTestSpacePrediction(boolean, boolean, boolean) - Method in class cc.mallet.fst.tests.TestCRF doTestSpacePrediction(boolean) - Method in class cc.mallet.fst.tests.TestMEMM doTestSpacePrediction(boolean, boolean, boolean) - Method in class cc.mallet.fst.tests.TestMEMM dotProduct(DenseVector) - Method in class cc.mallet.types.AugmentableFeatureVector dotProduct(SparseVector) - Method in class cc.mallet.types.AugmentableFeatureVector dotProduct(AugmentableFeatureVector) - Method in class cc.mallet.types.AugmentableFeatureVector dotProduct(ConstantMatrix) - Method in interface cc.mallet.types.ConstantMatrix dotProduct(ConstantMatrix) - Method in class cc.mallet.types.DenseMatrix dotProduct(int, Matrix2, int) - Method in class cc.mallet.types.FeatureVectorSequence dotProduct(int, Vector) - Method in class cc.mallet.types.FeatureVectorSequence dotProduct(DenseVector) - Method in class cc.mallet.types.HashedSparseVector dotProduct(SparseVector) - Method in class cc.mallet.types.HashedSparseVector dotProduct(DenseVector) - Method in class cc.mallet.types.IndexedSparseVector dotProduct(SparseVector) - Method in class cc.mallet.types.IndexedSparseVector dotProduct(double[], double[]) - Static method in class cc.mallet.types.MatrixOps dotProduct(ConstantMatrix) - Method in class cc.mallet.types.SparseMatrixn dotProduct(double[]) - Method in class cc.mallet.types.SparseVector VECTOR OPERATIONS dotProduct(ConstantMatrix) - Method in class cc.mallet.types.SparseVector dotProduct(DenseVector) - Method in class cc.mallet.types.SparseVector dotProduct(SparseVector) - Method in class cc.mallet.types.SparseVector doubleArrayToString(double[], int) - Static method in class cc.mallet.util.MVNormal Create a string representation of a square matrix in one-dimensional array format DoubleList - Class in cc.mallet.util DoubleList() - Constructor for class cc.mallet.util.DoubleList DoubleList(int) - Constructor for class cc.mallet.util.DoubleList DoubleList(int, double) - Constructor for class cc.mallet.util.DoubleList DoubleList(double[], int) - Constructor for class cc.mallet.util.DoubleList DoubleList(double[]) - Constructor for class cc.mallet.util.DoubleList drawObservation(int) - Method in class cc.mallet.types.Dirichlet Dirichlet-multinomial: draw a distribution from the dirichlet, then draw n samples from that multinomial. drawObservation(int, double[]) - Method in class cc.mallet.types.Dirichlet Draw a count vector from the probability distribution provided. drawObservations(int, int) - Method in class cc.mallet.types.Dirichlet Create a set of d draws from a dirichlet-multinomial, each with an average of n observations. dualLattice2html(PrintWriter, String, LatticeViewer.ExtorInfo, LatticeViewer.ExtorInfo) - Static method in class cc.mallet.extract.LatticeViewer dump() - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation dump(PrintWriter) - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation dump() - Method in class cc.mallet.grmm.inference.AbstractInferencer dump() - Method in class cc.mallet.grmm.inference.gbp.ParentChildGBP dump() - Method in interface cc.mallet.grmm.inference.Inferencer dump() - Method in class cc.mallet.grmm.inference.JunctionTree dump() - Method in class cc.mallet.grmm.inference.JunctionTreeInferencer dump() - Method in class cc.mallet.grmm.inference.MessageArray dump(PrintWriter) - Method in class cc.mallet.grmm.inference.MessageArray dump() - Method in class cc.mallet.grmm.types.Assignment dump(PrintWriter) - Method in class cc.mallet.grmm.types.Assignment dump() - Method in class cc.mallet.grmm.types.BidirectionalIntObjectMap dump(PrintStream) - Method in class cc.mallet.grmm.types.BidirectionalIntObjectMap dump(PrintWriter) - Method in class cc.mallet.grmm.types.BidirectionalIntObjectMap dump() - Method in class cc.mallet.grmm.types.FactorGraph Dumps all the variables and factors of the model to System.out in human-readable text. dump(PrintWriter) - Method in class cc.mallet.grmm.types.FactorGraph dump() - Method in class cc.mallet.types.Alphabet dump(PrintStream) - Method in class cc.mallet.types.Alphabet dump(PrintWriter) - Method in class cc.mallet.types.Alphabet dumpLogJoint(Assignment) - Method in class cc.mallet.grmm.inference.JunctionTree dumpLogJoint(Assignment) - Method in class cc.mallet.grmm.inference.JunctionTreeInferencer dumpNumeric() - Method in class cc.mallet.grmm.types.Assignment dumpToString() - Method in class cc.mallet.grmm.types.AbstractTableFactor dumpToString() - Method in class cc.mallet.grmm.types.Assignment dumpToString() - Method in class cc.mallet.grmm.types.BetaFactor dumpToString() - Method in class cc.mallet.grmm.types.BinaryUnaryFactor dumpToString() - Method in class cc.mallet.grmm.types.ConstantFactor dumpToString() - Method in class cc.mallet.grmm.types.CPT dumpToString() - Method in interface cc.mallet.grmm.types.Factor dumpToString() - Method in class cc.mallet.grmm.types.FactorGraph dumpToString() - Method in class cc.mallet.grmm.types.NormalFactor dumpToString() - Method in class cc.mallet.grmm.types.PottsTableFactor dumpToString() - Method in class cc.mallet.grmm.types.SkeletonFactor dumpToString() - Method in class cc.mallet.grmm.types.Tree dumpToString() - Method in class cc.mallet.grmm.types.UniformFactor dumpToString() - Method in class cc.mallet.grmm.types.UniNormalFactor dumpToString(Collection, String) - Static method in class cc.mallet.util.CollectionUtils dumpToString(Collection) - Static method in class cc.mallet.util.CollectionUtils dumpUnrolledGraphs(InstanceList) - Method in class cc.mallet.grmm.learning.ACRF duplicate() - Method in class cc.mallet.grmm.inference.AbstractInferencer duplicate() - Method in interface cc.mallet.grmm.inference.Inferencer duplicate() - Method in class cc.mallet.grmm.inference.MessageArray duplicate() - Method in class cc.mallet.grmm.types.AbstractTableFactor duplicate() - Method in class cc.mallet.grmm.types.Assignment duplicate() - Method in class cc.mallet.grmm.types.BetaFactor duplicate() - Method in class cc.mallet.grmm.types.BinaryUnaryFactor duplicate() - Method in class cc.mallet.grmm.types.BoltzmannPairFactor duplicate() - Method in class cc.mallet.grmm.types.BoltzmannUnaryFactor duplicate() - Method in class cc.mallet.grmm.types.ConstantFactor duplicate() - Method in class cc.mallet.grmm.types.CPT duplicate() - Method in interface cc.mallet.grmm.types.Factor duplicate() - Method in class cc.mallet.grmm.types.FactorGraph Returns a copy of this model. duplicate() - Method in class cc.mallet.grmm.types.LogTableFactor duplicate() - Method in class cc.mallet.grmm.types.NormalFactor duplicate() - Method in class cc.mallet.grmm.types.PottsTableFactor duplicate() - Method in class cc.mallet.grmm.types.SkeletonFactor duplicate() - Method in class cc.mallet.grmm.types.TableFactor duplicate() - Method in class cc.mallet.grmm.types.UniformFactor duplicate() - Method in class cc.mallet.grmm.types.UniNormalFactor E elapsedTime() - Method in class cc.mallet.util.Timing Returns how much time as passed since Object creation, or the most recent call to tick(). elementAt(int) - Method in class cc.mallet.util.Univariate elementwiseAccuracy(Sequence) - Method in interface cc.mallet.fst.MaxLattice elementwiseAccuracy(Sequence) - Method in class cc.mallet.fst.MaxLatticeDefault elementwiseAccuracy(Sequence, Sequence) - Static method in class cc.mallet.util.Sequences elementwiseDivideEquals(ConstantMatrix) - Method in class cc.mallet.types.DenseMatrix elementwiseDivideEquals(ConstantMatrix, double) - Method in class cc.mallet.types.DenseMatrix elementwiseDivideEquals(ConstantMatrix) - Method in interface cc.mallet.types.Matrix elementwiseDivideEquals(ConstantMatrix, double) - Method in interface cc.mallet.types.Matrix elementwiseDivideEquals(ConstantMatrix) - Method in class cc.mallet.types.SparseMatrixn elementwiseDivideEquals(ConstantMatrix, double) - Method in class cc.mallet.types.SparseMatrixn elementwiseTimesEquals(ConstantMatrix) - Method in class cc.mallet.types.DenseMatrix elementwiseTimesEquals(ConstantMatrix, double) - Method in class cc.mallet.types.DenseMatrix elementwiseTimesEquals(ConstantMatrix) - Method in interface cc.mallet.types.Matrix elementwiseTimesEquals(ConstantMatrix, double) - Method in interface cc.mallet.types.Matrix elementwiseTimesEquals(ConstantMatrix) - Method in class cc.mallet.types.SparseMatrixn elementwiseTimesEquals(ConstantMatrix, double) - Method in class cc.mallet.types.SparseMatrixn empiricalLikelihood(int, InstanceList) - Method in class cc.mallet.topics.HierarchicalLDA For use with empirical likelihood evaluation: sample a path through the tree, then sample a multinomial over topics in that path, then return a weighted sum of words. empiricalLikelihood(int, InstanceList) - Method in class cc.mallet.topics.LDAHyper Deprecated. EMPTY_DROP - Static variable in class cc.mallet.cluster.KMeans Drop an empty cluster EMPTY_ERROR - Static variable in class cc.mallet.cluster.KMeans Treat an empty cluster as an error condition. EMPTY_SINGLE - Static variable in class cc.mallet.cluster.KMeans Place the single instance furthest from the previous cluster mean EmptyInstanceIterator - Class in cc.mallet.pipe.iterator EmptyInstanceIterator() - Constructor for class cc.mallet.pipe.iterator.EmptyInstanceIterator enableDoubleBuffering(Component) - Static method in class cc.mallet.util.PrintUtilities Re-enables double buffering globally. endsPrematurely() - Method in class cc.mallet.fst.Segment EnronMessage2TokenSequence - Class in cc.mallet.share.weili.ner.enron EnronMessage2TokenSequence() - Constructor for class cc.mallet.share.weili.ner.enron.EnronMessage2TokenSequence ensureCapacity(int) - Method in class cc.mallet.types.MultiInstanceList ensureCapacity(int) - Method in class cc.mallet.types.Multinomial.Estimator ensureOperandCompatible(DiscreteFactor) - Method in class cc.mallet.grmm.types.AbstractTableFactor Ensures that this.inLogSpace == ptl.inLogSpace. entropy - Variable in class cc.mallet.fst.semi_supervised.EntropyLattice entropy() - Method in class cc.mallet.grmm.inference.JunctionTree entropy() - Method in class cc.mallet.grmm.types.AbstractFactor entropy() - Method in class cc.mallet.grmm.types.AbstractTableFactor entropy() - Method in class cc.mallet.grmm.types.CPT entropy() - Method in interface cc.mallet.grmm.types.Factor Returns the expected log factor value, i.e., sum_x factor.value(x) * Math.log (factor.value (x)) where the summation is taken over all passible assignments. entropy() - Method in class cc.mallet.grmm.types.FactorGraph entropy(FactorGraph) - Static method in class cc.mallet.grmm.util.Models Computes the exact entropy of a factor graph distribution using the junction tree algorithm. EntropyLattice - Class in cc.mallet.fst.semi_supervised Runs subsequence constrained forward-backward to compute the entropy of label sequences. EntropyLattice(FeatureVectorSequence, double[][], double[][][], Transducer, Transducer.Incrementor, double) - Constructor for class cc.mallet.fst.semi_supervised.EntropyLattice Runs constrained forward-backward. EntropyLattice.LatticeNode - Class in cc.mallet.fst.semi_supervised Contains alpha, beta values at a particular input position and state pair. entryClass() - Method in class cc.mallet.types.Alphabet entrySet() - Method in class cc.mallet.grmm.util.THashMultiMap EPSILON - Static variable in class cc.mallet.util.Maths Numbers that are closer than this are considered equal by almostEquals. equals(Object) - Method in class cc.mallet.cluster.Clustering equals(Object) - Method in class cc.mallet.fst.Segment equals(Object) - Method in class cc.mallet.grmm.types.BinaryUnaryFactor equals(Object) - Method in class cc.mallet.grmm.types.BoltzmannPairFactor equals(Object) - Method in class cc.mallet.grmm.types.BoltzmannUnaryFactor equals(Object) - Method in class cc.mallet.grmm.types.HashVarSet equals(Object) - Method in class cc.mallet.grmm.types.ListVarSet equals(Object) - Method in class cc.mallet.grmm.types.PottsTableFactor equals(Object) - Method in class cc.mallet.grmm.types.UnmodifiableVarSet equals(Object) - Method in class cc.mallet.types.Label equals(Object) - Method in class cc.mallet.types.Matrixn equals(Object) - Method in class cc.mallet.types.MultiInstanceList equals(Object) - Method in class cc.mallet.types.SparseMatrixn equals(boolean[][], boolean[][]) - Static method in class cc.mallet.util.ArrayUtils equalsPlus(double, ConstantMatrix) - Method in class cc.mallet.types.DenseMatrix equalsPlus(double, ConstantMatrix) - Method in interface cc.mallet.types.Matrix equalsPlus(double, ConstantMatrix) - Method in class cc.mallet.types.SparseMatrixn estimate() - Method in class cc.mallet.fst.FeatureTransducer estimate() - Method in class cc.mallet.fst.HMM estimate(int) - Method in class cc.mallet.topics.DMRTopicModel estimate(int) - Method in class cc.mallet.topics.HierarchicalLDA estimate(InstanceList, InstanceList, int, int, int, int, String, Randoms) - Method in class cc.mallet.topics.HierarchicalPAM estimate(InstanceList, int, int, int, String, Randoms) - Method in class cc.mallet.topics.LDA Deprecated. estimate(int, int, int, int, int, String, Randoms) - Method in class cc.mallet.topics.LDA Deprecated. estimate() - Method in class cc.mallet.topics.LDAHyper Deprecated. estimate(int) - Method in class cc.mallet.topics.LDAHyper Deprecated. estimate(InstanceList, int, int, int, int, String, Randoms) - Method in class cc.mallet.topics.PAM4L estimate() - Method in class cc.mallet.topics.ParallelTopicModel estimate() - Method in class cc.mallet.topics.PolylingualTopicModel estimate(int) - Method in class cc.mallet.topics.PolylingualTopicModel estimate(InstanceList, int, int, int, String, Randoms) - Method in class cc.mallet.topics.TopicalNGrams estimate() - Method in class cc.mallet.types.Dirichlet.Estimator estimate() - Method in class cc.mallet.types.Dirichlet.MethodOfMomentsEstimator estimate() - Method in class cc.mallet.types.Multinomial.Estimator estimate() - Method in class cc.mallet.types.Multinomial.MAPEstimator estimate() - Method in class cc.mallet.types.Multinomial.MEstimator estimateAll(int) - Method in class cc.mallet.topics.LDAStream estimateConfidence(Extraction) - Method in class cc.mallet.extract.ExtractionConfidenceEstimator estimateConfidence(DocumentExtraction) - Method in class cc.mallet.extract.ExtractionConfidenceEstimator estimateConfidence(DocumentExtraction) - Method in class cc.mallet.extract.TransducerExtractionConfidenceEstimator estimateConfidenceFor(Segment, SumLatticeDefault) - Method in class cc.mallet.fst.confidence.ConstrainedForwardBackwardConfidenceEstimator Calculates the confidence in the tagging of a Segment. estimateConfidenceFor(Segment, SumLatticeDefault) - Method in class cc.mallet.fst.confidence.GammaAverageConfidenceEstimator Calculates the confidence in the tagging of a Segment. estimateConfidenceFor(Segment, SumLatticeDefault) - Method in class cc.mallet.fst.confidence.GammaProductConfidenceEstimator Calculates the confidence in the tagging of a Segment. estimateConfidenceFor(Segment, SumLatticeDefault) - Method in class cc.mallet.fst.confidence.MaxEntConfidenceEstimator Calculates the confidence in the tagging of a Segment. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.MaxEntSequenceConfidenceEstimator Calculates the confidence in the tagging of an Instance. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.MinSegmentConfidenceEstimator Calculates the confidence in the tagging of a Instance. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.NBestViterbiConfidenceEstimator Calculates the confidence in the tagging of a Instance. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.QBCSequenceConfidenceEstimator Calculates the confidence in the tagging of a Instance. estimateConfidenceFor(Segment, SumLatticeDefault) - Method in class cc.mallet.fst.confidence.RandomConfidenceEstimator Randomly generate the confidence in the tagging of a Segment. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.RandomSequenceConfidenceEstimator Calculates the confidence in the tagging of an Instance. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.SegmentProductConfidenceEstimator Calculates the confidence in the tagging of a Instance. estimateConfidenceFor(Segment) - Method in class cc.mallet.fst.confidence.TransducerConfidenceEstimator Calculates the confidence in the tagging of a Segment. estimateConfidenceFor(Segment, SumLatticeDefault) - Method in class cc.mallet.fst.confidence.TransducerConfidenceEstimator estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.TransducerSequenceConfidenceEstimator Calculates the confidence in the tagging of a Sequence. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.ViterbiConfidenceEstimator Calculates the confidence in the tagging of a Instance. estimateConfidenceFor(Instance, Object[], Object[]) - Method in class cc.mallet.fst.confidence.ViterbiRatioConfidenceEstimator Calculates the confidence in the tagging of an Instance. euclideanDistance(AbstractTableFactor, AbstractTableFactor) - Static method in class cc.mallet.grmm.types.Factors euclideanDistance(SparseVector, SparseVector) - Method in class cc.mallet.types.Minkowski EULER_MASCHERONI - Static variable in class cc.mallet.types.Dirichlet Actually the negative Euler-Mascheroni constant evaluate(ClassifierTrainer) - Method in class cc.mallet.classify.ClassifierEvaluator Evaluates a ClassifierTrainer and its Classifier on the instance lists specified in the constructor. evaluate(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.AccuracyEvaluator evaluate(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.BCubedEvaluator evaluate(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluator evaluate(Clustering[], Clustering[]) - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluator evaluate(Clustering[], Clusterer) - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluator evaluate(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluators evaluate(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.MUCEvaluator evaluate(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.PairF1Evaluator evaluate(Neighbor) - Method in class cc.mallet.cluster.neighbor_evaluator.ClassifyingNeighborEvaluator evaluate(Neighbor[]) - Method in class cc.mallet.cluster.neighbor_evaluator.ClassifyingNeighborEvaluator evaluate(Neighbor[]) - Method in class cc.mallet.cluster.neighbor_evaluator.MedoidEvaluator evaluate(Neighbor) - Method in class cc.mallet.cluster.neighbor_evaluator.MedoidEvaluator evaluate(Neighbor) - Method in interface cc.mallet.cluster.neighbor_evaluator.NeighborEvaluator evaluate(Neighbor[]) - Method in interface cc.mallet.cluster.neighbor_evaluator.NeighborEvaluator evaluate(Neighbor[]) - Method in class cc.mallet.cluster.neighbor_evaluator.PairwiseEvaluator evaluate(Neighbor) - Method in class cc.mallet.cluster.neighbor_evaluator.PairwiseEvaluator evaluate(Neighbor) - Method in class cc.mallet.cluster.neighbor_evaluator.RandomEvaluator evaluate(Neighbor[]) - Method in class cc.mallet.cluster.neighbor_evaluator.RandomEvaluator evaluate(Neighbor) - Method in class cc.mallet.cluster.neighbor_evaluator.RankingNeighborEvaluator evaluate(Neighbor[]) - Method in class cc.mallet.cluster.neighbor_evaluator.RankingNeighborEvaluator evaluate(Extraction) - Method in class cc.mallet.extract.AccuracyCoverageEvaluator evaluate(String, Extraction, PrintStream) - Method in class cc.mallet.extract.AccuracyCoverageEvaluator evaluate(Extraction) - Method in interface cc.mallet.extract.ExtractionEvaluator evaluate(Extraction) - Method in class cc.mallet.extract.PerDocumentF1Evaluator evaluate(Extraction, PrintStream) - Method in class cc.mallet.extract.PerDocumentF1Evaluator evaluate(Extraction, PrintWriter) - Method in class cc.mallet.extract.PerDocumentF1Evaluator evaluate(String, Extraction, PrintWriter) - Method in class cc.mallet.extract.PerDocumentF1Evaluator evaluate(Extraction) - Method in class cc.mallet.extract.PerFieldF1Evaluator evaluate(String, Extraction, PrintStream) - Method in class cc.mallet.extract.PerFieldF1Evaluator evaluate(Transducer, ArrayList, InstanceList, ArrayList, String, PrintStream, boolean) - Method in class cc.mallet.fst.confidence.ConfidenceCorrectorEvaluator Only evaluates over sequences which contain errors. evaluate(TransducerEvaluator, InstanceList) - Method in class cc.mallet.fst.CRF Deprecated. evaluate(TransducerTrainer) - Method in class cc.mallet.fst.TransducerEvaluator Evaluates a TransducerTrainer and its Transducer on the instance lists specified in the constructor. evaluate(ACRF, int, InstanceList, InstanceList, InstanceList) - Method in class cc.mallet.grmm.learning.ACRFEvaluator Evalutes the model in the middle of training. evaluate(ACRF, int, InstanceList, InstanceList, InstanceList) - Method in class cc.mallet.grmm.learning.AcrfSerialEvaluator evaluate(ACRF, int, InstanceList, InstanceList, InstanceList) - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer.FileEvaluator evaluate(ACRF, int, InstanceList, InstanceList, InstanceList) - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer.LogEvaluator evaluate(ACRF, int, InstanceList, InstanceList, InstanceList) - Method in class cc.mallet.grmm.learning.MultiSegmentationEvaluatorACRF evaluate(Optimizable.ByBatchGradient, int, int, int, int[]) - Method in interface cc.mallet.optimize.OptimizerEvaluator.ByBatchGradient Performs some operation at the end of every batch. evaluate(Optimizable.ByGradientValue, int) - Method in interface cc.mallet.optimize.OptimizerEvaluator.ByGradient Performs some operation at the end of each iteration of a maximizer. evaluateInstanceList(ClassifierTrainer, InstanceList, String) - Method in class cc.mallet.classify.ClassifierAccuracyEvaluator evaluateInstanceList(ClassifierTrainer, InstanceList, String) - Method in class cc.mallet.classify.ClassifierEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.CRFWriter evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.InstanceAccuracyEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.LabelDistributionEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.MultiSegmentationEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.PerClassAccuracyEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.SegmentationEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.TokenAccuracyEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.TransducerEvaluator evaluateInstanceList(TransducerTrainer, InstanceList, String) - Method in class cc.mallet.fst.ViterbiWriter evaluateLeftToRight(InstanceList, int, boolean, PrintStream) - Method in class cc.mallet.topics.MarginalProbEstimator EvaluateTopics - Class in cc.mallet.topics.tui EvaluateTopics() - Constructor for class cc.mallet.topics.tui.EvaluateTopics evaluateTotals() - Method in class cc.mallet.cluster.evaluate.AccuracyEvaluator evaluateTotals() - Method in class cc.mallet.cluster.evaluate.BCubedEvaluator evaluateTotals() - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluator evaluateTotals() - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluators evaluateTotals() - Method in class cc.mallet.cluster.evaluate.MUCEvaluator evaluateTotals() - Method in class cc.mallet.cluster.evaluate.PairF1Evaluator evaluator - Variable in class cc.mallet.cluster.HillClimbingClusterer evaluator - Variable in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer ewensLikelihoodRatio(int[], int[], double) - Static method in class cc.mallet.types.Dirichlet Similar to the Dirichlet-multinomial test,s this is a likelihood ratio based on the Ewens Sampling Formula, which can be considered the distribution of partitions of integers generated by the Chinese restaurant process. ExactMatchComparator - Class in cc.mallet.extract Created: Nov 23, 2004 ExactMatchComparator() - Constructor for class cc.mallet.extract.ExactMatchComparator ExactSampler - Class in cc.mallet.grmm.inference Computes an exact sample from the distribution of a given factor graph by forming a junction tree. ExactSampler() - Constructor for class cc.mallet.grmm.inference.ExactSampler ExactSampler(Randoms) - Constructor for class cc.mallet.grmm.inference.ExactSampler Examples - Class in cc.mallet.util.resources.wn A class to demonstrate the functionality of the JWNL package. Examples() - Constructor for class cc.mallet.util.resources.wn.Examples executor - Variable in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR executor - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL exp() - Static method in class cc.mallet.grmm.util.Flops exp(int) - Static method in class cc.mallet.grmm.util.Flops exp() - Method in class cc.mallet.types.LogNumber EXP_GAIN - Static variable in class cc.mallet.classify.MCMaxEntTrainer expectation - Variable in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints.MaxEntFLGEConstraint expectation - Variable in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints.MaxEntL2IndGEConstraint expectation - Variable in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints.MaxEntFLPRConstraint expectation - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints.OneLabelGEConstraint expectation - Variable in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints.OneLabelL2IndGEConstraint expectation - Variable in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints.TwoLabelGEConstraint expectation - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint expectation - Variable in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints.OneLabelPRConstraint expectations - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood expectations - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood expectations - Variable in class cc.mallet.fst.CRFTrainerByStochasticGradient expectations - Variable in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization expectations - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL ExpGain - Class in cc.mallet.types ExpGain(InstanceList, LabelVector[], double) - Constructor for class cc.mallet.types.ExpGain ExpGain(InstanceList, Classification[], double) - Constructor for class cc.mallet.types.ExpGain ExpGain.Factory - Class in cc.mallet.types ExpGain.Factory(LabelVector[]) - Constructor for class cc.mallet.types.ExpGain.Factory ExpGain.Factory(LabelVector[], double) - Constructor for class cc.mallet.types.ExpGain.Factory expNormalize(double[]) - Static method in class cc.mallet.types.MatrixOps exponentiate(double) - Method in class cc.mallet.grmm.types.AbstractFactor exponentiate(double) - Method in class cc.mallet.grmm.types.CPT exponentiate(double) - Method in interface cc.mallet.grmm.types.Factor exponentiate(double) - Method in class cc.mallet.grmm.types.FactorGraph exponentiate(double) - Method in class cc.mallet.grmm.types.LogTableFactor exponentiate(double) - Method in class cc.mallet.grmm.types.TableFactor extend(int[], int) - Static method in class cc.mallet.util.ArrayUtils Returns a new array containing all of a, with additional extra space added (zero initialized). extend(double[], int) - Static method in class cc.mallet.util.ArrayUtils Returns a new array containing all of a, with additional extra space added (zero initialized). extendedDotProduct(DenseVector) - Method in class cc.mallet.types.SparseVector extendedDotProduct(SparseVector) - Method in class cc.mallet.types.SparseVector extract(Object) - Method in class cc.mallet.extract.CRFExtractor extract(Tokenization) - Method in class cc.mallet.extract.CRFExtractor extract(InstanceList) - Method in class cc.mallet.extract.CRFExtractor Assumes Instance.source contains the Tokenization object. extract(Iterator<Instance>) - Method in class cc.mallet.extract.CRFExtractor extract(Object) - Method in interface cc.mallet.extract.Extractor Performs extraction given a raw object. extract(Tokenization) - Method in interface cc.mallet.extract.Extractor Performs extraction from an object that has been already been tokenized. extract(Iterator<Instance>) - Method in interface cc.mallet.extract.Extractor Performs extraction on a a set of raw documents. extract(Object) - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor extract(Tokenization) - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor extract(Iterator<Instance>) - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor extract(InstanceList) - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor Extraction - Class in cc.mallet.extract The results of doing information extraction. Extraction(Extractor, LabelAlphabet) - Constructor for class cc.mallet.extract.Extraction Creates an empty Extraction option. Extraction(Extractor, LabelAlphabet, String, Tokenization, Sequence, String) - Constructor for class cc.mallet.extract.Extraction Creates an extration given a sequence output by some kind of per-sequece labeler, like an HMM or a CRF. extraction2html(Extraction, CRFExtractor, PrintStream) - Static method in class cc.mallet.extract.LatticeViewer extraction2html(Extraction, CRFExtractor, PrintWriter) - Static method in class cc.mallet.extract.LatticeViewer extraction2html(Extraction, CRFExtractor, PrintStream, boolean) - Static method in class cc.mallet.extract.LatticeViewer extraction2html(Extraction, CRFExtractor, PrintWriter, boolean) - Static method in class cc.mallet.extract.LatticeViewer ExtractionConfidenceEstimator - Class in cc.mallet.extract Estimates the confidence in the labeling of a LabeledSpan. ExtractionConfidenceEstimator() - Constructor for class cc.mallet.extract.ExtractionConfidenceEstimator ExtractionEvaluator - Interface in cc.mallet.extract Created: Oct 8, 2004 extractMax(Variable[]) - Method in class cc.mallet.grmm.types.AbstractFactor extractMax(Collection) - Method in class cc.mallet.grmm.types.AbstractFactor extractMax(Variable) - Method in class cc.mallet.grmm.types.AbstractFactor extractMax(Variable) - Method in class cc.mallet.grmm.types.AbstractTableFactor extractMax(Variable[]) - Method in class cc.mallet.grmm.types.AbstractTableFactor extractMax(Collection) - Method in class cc.mallet.grmm.types.AbstractTableFactor extractMax(Collection) - Method in class cc.mallet.grmm.types.CPT extractMax(Variable) - Method in class cc.mallet.grmm.types.CPT extractMax(Variable[]) - Method in class cc.mallet.grmm.types.CPT extractMax(Collection) - Method in interface cc.mallet.grmm.types.Factor Returns a potential phi over the given variables obtained by taking phi (x) = max_[all v that contain x] this.prob (x) extractMax(Variable) - Method in interface cc.mallet.grmm.types.Factor Returns a potential phi over the given variables obtained by taking phi (x) = max_[all v that contain x] this.prob (x) extractMax(Variable[]) - Method in interface cc.mallet.grmm.types.Factor Returns a potential phi over the given variables obtained by taking phi (x) = max_[all v that contain x] this.prob (x) extractMax(Collection) - Method in class cc.mallet.grmm.types.FactorGraph extractMax(Variable) - Method in class cc.mallet.grmm.types.FactorGraph extractMax(Variable[]) - Method in class cc.mallet.grmm.types.FactorGraph extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.AbstractFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.Assignment extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.BetaFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.BinaryUnaryFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.ConstantFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.NormalFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.PottsTableFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.SkeletonFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.UniformFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.UniNormalFactor extractMin() - Method in class cc.mallet.util.search.MinHeap extractMin() - Method in interface cc.mallet.util.search.PriorityQueue Remove the top element of the queue. extractOnTestData(ACRFExtractor) - Method in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer Extractor - Interface in cc.mallet.extract Generic interface for objects that do information extraction. F f(Object) - Method in interface cc.mallet.util.CollectionUtils.Fn f1 - Variable in class cc.mallet.grmm.learning.DefaultAcrfTrainer.TestResults Factor - Interface in cc.mallet.grmm.types Interface for multivariate discrete probability distributions. FactorGraph - Class in cc.mallet.grmm.types Class for undirected graphical models. FactorGraph() - Constructor for class cc.mallet.grmm.types.FactorGraph FactorGraph(Variable[]) - Constructor for class cc.mallet.grmm.types.FactorGraph Create a model with the variables given. FactorGraph(Factor[]) - Constructor for class cc.mallet.grmm.types.FactorGraph FactorGraph(Collection) - Constructor for class cc.mallet.grmm.types.FactorGraph FactorGraph(int) - Constructor for class cc.mallet.grmm.types.FactorGraph Create a model with the given capacity (i.e., capacityin terms of number of variable nodes). factorial(int) - Static method in class cc.mallet.util.Maths FactorizedRegion - Class in cc.mallet.grmm.inference.gbp A more space-efficient Region class that doesn't maintain a global factor over all assignments to the region. FactorizedRegion(List) - Constructor for class cc.mallet.grmm.inference.gbp.FactorizedRegion factorOf(VarSet) - Method in class cc.mallet.grmm.types.FactorGraph Returns the factor in this graph, if any, whose domain is a given clique. factorOf(Variable, Variable) - Method in class cc.mallet.grmm.types.FactorGraph Returns the factor defined over a given pair of variables. factorOf(Variable) - Method in class cc.mallet.grmm.types.FactorGraph Returns the factor for a given node. factorOf(Collection) - Method in class cc.mallet.grmm.types.FactorGraph Searches the graphical model for a factor over the given collection of variables. factorProduct(Assignment) - Method in class cc.mallet.grmm.types.FactorGraph Returns the unnormalized probability for an assignment to the model. factors - Variable in class cc.mallet.grmm.learning.DefaultAcrfTrainer.TestResults factors() - Method in class cc.mallet.grmm.types.FactorGraph Returns collection that contains factors in this model. Factors - Class in cc.mallet.grmm.types A static utility class containing utility methods for dealing with factors, especially TableFactor objects. Factors() - Constructor for class cc.mallet.grmm.types.Factors factorsIterator() - Method in class cc.mallet.grmm.types.FactorGraph Returns an iterator of all the factors in the graph. FALSE_NEGATIVE - Static variable in class cc.mallet.types.ROCData FALSE_POSITIVE - Static variable in class cc.mallet.types.ROCData FeatureConjunction - Class in cc.mallet.types FeatureConjunction(String, Alphabet, int[], boolean[], boolean, boolean, boolean) - Constructor for class cc.mallet.types.FeatureConjunction If negations[i] is true, insist that the feature has non-zero value; if false, insist that it has zero value. FeatureConjunction(String, Alphabet, int[], boolean[], boolean) - Constructor for class cc.mallet.types.FeatureConjunction FeatureConjunction(String, Alphabet, int[], boolean[]) - Constructor for class cc.mallet.types.FeatureConjunction FeatureConjunction(Alphabet, int[], boolean[]) - Constructor for class cc.mallet.types.FeatureConjunction FeatureConjunction(Alphabet, int[]) - Constructor for class cc.mallet.types.FeatureConjunction FeatureConjunction.List - Class in cc.mallet.types FeatureConjunction.List() - Constructor for class cc.mallet.types.FeatureConjunction.List FeatureConstraintUtil - Class in cc.mallet.classify Utility functions for creating feature constraints that can be used with GE training. FeatureConstraintUtil() - Constructor for class cc.mallet.classify.FeatureConstraintUtil FeatureCounter - Class in cc.mallet.types Efficient, compact, incremental counting of features in an alphabet. FeatureCounter(Alphabet) - Constructor for class cc.mallet.types.FeatureCounter FeatureCounter - Class in cc.mallet.util FeatureCounter(InstanceList) - Constructor for class cc.mallet.util.FeatureCounter FeatureCountPipe - Class in cc.mallet.pipe Pruning low-count features can be a good way to save memory and computation. FeatureCountPipe() - Constructor for class cc.mallet.pipe.FeatureCountPipe FeatureCountPipe(Alphabet, Alphabet) - Constructor for class cc.mallet.pipe.FeatureCountPipe FeatureCounts - Class in cc.mallet.types FeatureCounts(InstanceList) - Constructor for class cc.mallet.types.FeatureCounts FeatureCounts(Alphabet, double[]) - Constructor for class cc.mallet.types.FeatureCounts FeatureCounts.Factory - Class in cc.mallet.types FeatureCounts.Factory() - Constructor for class cc.mallet.types.FeatureCounts.Factory FeatureDocFreqPipe - Class in cc.mallet.pipe Pruning low-count features can be a good way to save memory and computation. FeatureDocFreqPipe() - Constructor for class cc.mallet.pipe.FeatureDocFreqPipe FeatureDocFreqPipe(Alphabet, Alphabet) - Constructor for class cc.mallet.pipe.FeatureDocFreqPipe FeatureInducer - Class in cc.mallet.types FeatureInducer(RankedFeatureVector.Factory, InstanceList, int, int, int) - Constructor for class cc.mallet.types.FeatureInducer FeatureInducer(RankedFeatureVector.Factory, InstanceList, int) - Constructor for class cc.mallet.types.FeatureInducer featureInducers - Variable in class cc.mallet.fst.CRF featurePipe - Variable in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer FeatureSelectingClassifierTrainer - Class in cc.mallet.classify Adaptor for adding feature selection to a classifier trainer. FeatureSelectingClassifierTrainer(ClassifierTrainer, FeatureSelector) - Constructor for class cc.mallet.classify.FeatureSelectingClassifierTrainer featureSelection - Variable in class cc.mallet.classify.MaxEnt featureSelection - Static variable in class cc.mallet.classify.tui.Vectors2FeatureConstraints FeatureSelection - Class in cc.mallet.types FeatureSelection(Alphabet, BitSet) - Constructor for class cc.mallet.types.FeatureSelection FeatureSelection(Alphabet) - Constructor for class cc.mallet.types.FeatureSelection FeatureSelection(RankedFeatureVector, int) - Constructor for class cc.mallet.types.FeatureSelection featureSelections - Variable in class cc.mallet.fst.CRF FeatureSelector - Class in cc.mallet.types FeatureSelector(RankedFeatureVector.Factory, int) - Constructor for class cc.mallet.types.FeatureSelector FeatureSelector(RankedFeatureVector.Factory, double) - Constructor for class cc.mallet.types.FeatureSelector FeatureSelector(RankedFeatureVector.PerLabelFactory, int) - Constructor for class cc.mallet.types.FeatureSelector FeatureSelector(RankedFeatureVector.PerLabelFactory, double) - Constructor for class cc.mallet.types.FeatureSelector FeatureSequence - Class in cc.mallet.types An implementation of Sequence that ensures that every Object in the sequence has the same class. FeatureSequence(Alphabet, int[]) - Constructor for class cc.mallet.types.FeatureSequence Creates a FeatureSequence given all of the objects in the sequence. FeatureSequence(Alphabet, int[], int) - Constructor for class cc.mallet.types.FeatureSequence FeatureSequence(Alphabet, int) - Constructor for class cc.mallet.types.FeatureSequence FeatureSequence(Alphabet) - Constructor for class cc.mallet.types.FeatureSequence FeatureSequence2AugmentableFeatureVector - Class in cc.mallet.pipe Convert the data field from a feature sequence to an augmentable feature vector. FeatureSequence2AugmentableFeatureVector(boolean) - Constructor for class cc.mallet.pipe.FeatureSequence2AugmentableFeatureVector FeatureSequence2AugmentableFeatureVector() - Constructor for class cc.mallet.pipe.FeatureSequence2AugmentableFeatureVector FeatureSequence2FeatureVector - Class in cc.mallet.pipe Convert the data field from a feature sequence to a feature vector. FeatureSequence2FeatureVector(boolean) - Constructor for class cc.mallet.pipe.FeatureSequence2FeatureVector FeatureSequence2FeatureVector() - Constructor for class cc.mallet.pipe.FeatureSequence2FeatureVector FeatureSequenceConvolution - Class in cc.mallet.pipe FeatureSequenceConvolution() - Constructor for class cc.mallet.pipe.FeatureSequenceConvolution FeatureSequenceWithBigrams - Class in cc.mallet.types A FeatureSequence with a parallel record of bigrams, kept in a separate dictionary FeatureSequenceWithBigrams(Alphabet, Alphabet, TokenSequence) - Constructor for class cc.mallet.types.FeatureSequenceWithBigrams featuresFile - Static variable in class cc.mallet.classify.tui.Vectors2FeatureConstraints FeaturesInWindow - Class in cc.mallet.pipe.tsf FeaturesInWindow(String, int, int, Pattern, boolean) - Constructor for class cc.mallet.pipe.tsf.FeaturesInWindow FeaturesInWindow(String, int, int) - Constructor for class cc.mallet.pipe.tsf.FeaturesInWindow equivalent to FeaturesInWindow((namePrefix, leftBoundaryOffset, rightBoundaryOffset, null, true); FeaturesOfFirstMention - Class in cc.mallet.pipe.tsf FeaturesOfFirstMention(String, String, Pattern) - Constructor for class cc.mallet.pipe.tsf.FeaturesOfFirstMention FeaturesOfFirstMention(String, Pattern, Pattern, boolean) - Constructor for class cc.mallet.pipe.tsf.FeaturesOfFirstMention FeaturesOfFirstMention(String, Pattern) - Constructor for class cc.mallet.pipe.tsf.FeaturesOfFirstMention FeaturesOfFirstMention(String) - Constructor for class cc.mallet.pipe.tsf.FeaturesOfFirstMention featuresOverlap(Alphabet, int, int) - Static method in class cc.mallet.types.FeatureConjunction FeatureTransducer - Class in cc.mallet.fst FeatureTransducer(Alphabet, Alphabet) - Constructor for class cc.mallet.fst.FeatureTransducer FeatureTransducer(Alphabet) - Constructor for class cc.mallet.fst.FeatureTransducer FeatureTransducer() - Constructor for class cc.mallet.fst.FeatureTransducer FeatureTransducer.State - Class in cc.mallet.fst FeatureTransducer.State(String, int, double, double, int[], int[], double[], String[], FeatureTransducer) - Constructor for class cc.mallet.fst.FeatureTransducer.State FeatureTransducer.Transition - Class in cc.mallet.fst FeatureTransducer.Transition(int, int, double, FeatureTransducer.State, String) - Constructor for class cc.mallet.fst.FeatureTransducer.Transition FeatureTransducer.TransitionIterator - Class in cc.mallet.fst FeatureTransducer.TransitionIterator(FeatureTransducer.State) - Constructor for class cc.mallet.fst.FeatureTransducer.TransitionIterator FeatureTransducer.TransitionIterator(FeatureTransducer.State, int) - Constructor for class cc.mallet.fst.FeatureTransducer.TransitionIterator FeatureValueString2FeatureVector - Class in cc.mallet.pipe FeatureValueString2FeatureVector(Alphabet) - Constructor for class cc.mallet.pipe.FeatureValueString2FeatureVector FeatureValueString2FeatureVector() - Constructor for class cc.mallet.pipe.FeatureValueString2FeatureVector FeatureVector - Class in cc.mallet.types A subset of an Alphabet in which each element of the subset has an associated value. FeatureVector(Alphabet, int[], double[], int, int, boolean, boolean, boolean) - Constructor for class cc.mallet.types.FeatureVector FeatureVector(Alphabet, double[]) - Constructor for class cc.mallet.types.FeatureVector Create a dense vector FeatureVector(Alphabet, int[], double[]) - Constructor for class cc.mallet.types.FeatureVector Create non-binary vector, possibly dense if "featureIndices" or possibly sparse, if not FeatureVector(Alphabet, int[]) - Constructor for class cc.mallet.types.FeatureVector Create binary vector FeatureVector(Alphabet, Object[], double[]) - Constructor for class cc.mallet.types.FeatureVector FeatureVector(FeatureSequence, boolean) - Constructor for class cc.mallet.types.FeatureVector FeatureVector(FeatureSequence) - Constructor for class cc.mallet.types.FeatureVector FeatureVector(Alphabet, PropertyList, boolean, boolean) - Constructor for class cc.mallet.types.FeatureVector FeatureVector(Alphabet, PropertyList, boolean) - Constructor for class cc.mallet.types.FeatureVector FeatureVector(FeatureVector, Alphabet, int[]) - Constructor for class cc.mallet.types.FeatureVector New feature vector containing all the features of "fv", plus new features created by making conjunctions between the features in "conjunctions" and all the other features. FeatureVector(FeatureVector, Alphabet, FeatureSelection, FeatureSelection) - Constructor for class cc.mallet.types.FeatureVector FeatureVectorConjunctions - Class in cc.mallet.pipe Include in the FeatureVector conjunctions of all its features. FeatureVectorConjunctions() - Constructor for class cc.mallet.pipe.FeatureVectorConjunctions FeatureVectorSequence - Class in cc.mallet.types FeatureVectorSequence(FeatureVector[]) - Constructor for class cc.mallet.types.FeatureVectorSequence FeatureVectorSequence(Alphabet, TokenSequence, boolean, boolean, boolean) - Constructor for class cc.mallet.types.FeatureVectorSequence FeatureVectorSequence(Alphabet, TokenSequence, boolean, boolean) - Constructor for class cc.mallet.types.FeatureVectorSequence FeatureVectorSequence(Alphabet, TokenSequence) - Constructor for class cc.mallet.types.FeatureVectorSequence FeatureVectorSequence.Iterator - Class in cc.mallet.types An iterator over the FeatureVectors in the sequence. FeatureVectorSequence.Iterator() - Constructor for class cc.mallet.types.FeatureVectorSequence.Iterator FeatureVectorSequence2FeatureVectors - Class in cc.mallet.pipe Given instances with a FeatureVectorSequence in the data field, break up the sequence into the individual FeatureVectors, producing one FeatureVector per Instance. FeatureVectorSequence2FeatureVectors() - Constructor for class cc.mallet.pipe.FeatureVectorSequence2FeatureVectors FeatureWindow - Class in cc.mallet.share.upenn.ner Adds all features of tokens in the window to the center token. FeatureWindow(int, int) - Constructor for class cc.mallet.share.upenn.ner.FeatureWindow Field - Class in cc.mallet.extract Created: Oct 12, 2004 Field(LabeledSpan) - Constructor for class cc.mallet.extract.Field fieldAlphabet() - Method in class cc.mallet.cluster.Record FieldCleaner - Interface in cc.mallet.extract Interface for functions that are used to clean up field values after extraction has been performed. FieldComparator - Interface in cc.mallet.extract Interface for functions that compares extracted values of a field to see if they match. fields() - Method in class cc.mallet.cluster.Record fieldsIterator() - Method in class cc.mallet.extract.Record FIFTY_PERCENT_INDEX - Static variable in class cc.mallet.topics.TopicModelDiagnostics FileIterator - Class in cc.mallet.pipe.iterator An iterator that generates instances from an initial directory or set of directories. FileIterator(File[], FileFilter, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileIterator Construct a FileIterator that will supply filenames within initial directories as instances FileIterator(File[], FileFilter, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(File[], Pattern) - Constructor for class cc.mallet.pipe.iterator.FileIterator Iterate over Files that pass the fileFilter test, setting... FileIterator(File[], Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String[], FileFilter) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String[], String) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String[], Pattern) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String[], Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(File, FileFilter, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(File, FileFilter, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(File, FileFilter) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(File, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(File, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(File) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileIterator(String, FileFilter) - Constructor for class cc.mallet.pipe.iterator.FileIterator FileListIterator - Class in cc.mallet.pipe.iterator An iterator that generates instances for a pipe from a list of filenames. FileListIterator(File[], FileFilter, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileListIterator Construct an iterator over the given arry of Files The instances constructed from the files are returned in the same order as they appear in the given array FileListIterator(String[], FileFilter, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileListIterator FileListIterator(File, FileFilter, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileListIterator Construct a FileListIterator with the file containing the list of files, which contains one filename per line. FileListIterator(File, File, FileFilter, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileListIterator Construct a FileListIterator with the file containing the list of files of RELATIVE pathnames, one filename per line. FileListIterator(String, FileFilter, Pattern, boolean) - Constructor for class cc.mallet.pipe.iterator.FileListIterator FileListIterator(String, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileListIterator Filename2CharSequence - Class in cc.mallet.pipe Given a filename contained in a string, read in contents of file into a CharSequence. Filename2CharSequence() - Constructor for class cc.mallet.pipe.Filename2CharSequence filenameToUriString(String) - Static method in class cc.mallet.util.UriUtils FileUriIterator - Class in cc.mallet.pipe.iterator FileUriIterator(File[], FileFilter, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileUriIterator FileUriIterator(File, FileFilter, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileUriIterator FileUriIterator(File[], Pattern) - Constructor for class cc.mallet.pipe.iterator.FileUriIterator FileUriIterator(File, Pattern) - Constructor for class cc.mallet.pipe.iterator.FileUriIterator FileUtils - Class in cc.mallet.util Contains static utilities for manipulating files. FilterEmptyFeatureVectors - Class in cc.mallet.pipe FilterEmptyFeatureVectors() - Constructor for class cc.mallet.pipe.FilterEmptyFeatureVectors finalProbList - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL finalWeights - Variable in class cc.mallet.fst.CRF.Factors findCluster(Variable[]) - Method in class cc.mallet.grmm.inference.JunctionTree Returns a cluster in the tree that contains exactly the given variables, or null if no such cluster exists. findParentCluster(Variable) - Method in class cc.mallet.grmm.inference.JunctionTree Returns a cluster in the tree that contains var. findParentCluster(Collection) - Method in class cc.mallet.grmm.inference.JunctionTree Returns a cluster in the tree that contains all the vars in a collection. findVariable(String) - Method in class cc.mallet.grmm.types.AbstractTableFactor findVariable(String) - Method in class cc.mallet.grmm.types.FactorGraph Searches this model for a variable with a given name. finishedTraining - Variable in class cc.mallet.classify.ClassifierTrainer FIRST_DIRECTORY - Static variable in class cc.mallet.pipe.iterator.FileIterator Use as label names the first directory in the filename. FIRST_DIRECTORY - Static variable in class cc.mallet.pipe.iterator.FileListIterator Use as label names the first directory in the filename. FIRST_DIRECTORY - Static variable in class cc.mallet.pipe.iterator.UnlabeledFileIterator Use as label names the first directory in the filename. FirstOrderClusterExample - Class in cc.mallet.cluster.examples Illustrates use of a supervised clustering method that uses features over clusters. FirstOrderClusterExample() - Constructor for class cc.mallet.cluster.examples.FirstOrderClusterExample five - Variable in class cc.mallet.util.Univariate Flops - Class in cc.mallet.grmm.util Utilities for flop (floating-point operation) counting. Flops() - Constructor for class cc.mallet.grmm.util.Flops Flops.Watch - Class in cc.mallet.grmm.util Flops.Watch() - Constructor for class cc.mallet.grmm.util.Flops.Watch forceStale() - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF forEach(TObjectProcedure, Object[]) - Static method in class cc.mallet.util.ArrayUtils forEach(TObjectProcedure, Object[][]) - Static method in class cc.mallet.util.ArrayUtils format(LogRecord) - Method in class cc.mallet.util.PlainLogFormatter format(LogRecord) - Method in class cc.mallet.util.ProgressMessageLogFormatter formatString() - Method in class cc.mallet.types.StringEditVector formatter - Variable in class cc.mallet.topics.LDAHyper Deprecated. formatter - Variable in class cc.mallet.topics.NPTopicModel formatter - Variable in class cc.mallet.topics.ParallelTopicModel formatter - Variable in class cc.mallet.topics.PolylingualTopicModel formatter - Variable in class cc.mallet.topics.SimpleLDA forwardLattice(double[][], double[][][]) - Method in class cc.mallet.fst.semi_supervised.EntropyLattice Computes the forward entropies (H^alpha). freezeWeights(int) - Method in class cc.mallet.fst.CRF Freezes a set of weights to their current values. freezeWeights(String) - Method in class cc.mallet.fst.CRF Freezes a set of weights to their current values. from() - Method in class cc.mallet.grmm.inference.MessageArray.Iterator FSTConstraintUtil - Class in cc.mallet.fst.semi_supervised Expectation constraint utilities for fst package. FSTConstraintUtil() - Constructor for class cc.mallet.fst.semi_supervised.FSTConstraintUtil FullMessageStrategy - Class in cc.mallet.grmm.inference.gbp A first implementation of MessageStrategy that assumes that a BP region graph is being used. FullMessageStrategy() - Constructor for class cc.mallet.grmm.inference.gbp.FullMessageStrategy G GainRatio - Class in cc.mallet.types List of features along with their thresholds sorted in descending order of the ratio of (1) information gained by splitting instances on the feature at its associated threshold value, to (2) the split information. GainRatio(Alphabet, double[], double[], double, LabelVector, int, int) - Constructor for class cc.mallet.types.GainRatio gamma - Static variable in class cc.mallet.classify.tests.TestStaticParameters.Factory gamma - Variable in class cc.mallet.topics.NPTopicModel gamma(double) - Static method in class cc.mallet.util.Maths GammaAverageConfidenceEstimator - Class in cc.mallet.fst.confidence Calculates the confidence in an extracted segment by taking the average of P(s_i|o) for each state in the segment. GammaAverageConfidenceEstimator(Transducer) - Constructor for class cc.mallet.fst.confidence.GammaAverageConfidenceEstimator GammaProductConfidenceEstimator - Class in cc.mallet.fst.confidence Calculates the confidence in an extracted segment by taking the product of eP(s_i|o) for each state in the segment. GammaProductConfidenceEstimator(Transducer) - Constructor for class cc.mallet.fst.confidence.GammaProductConfidenceEstimator gammas - Variable in class cc.mallet.fst.semi_supervised.pr.SumLatticePR gatherConstraints(InstanceList) - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood Set the constraints by running forward-backward with the output label sequence provided, thus restricting it to only those paths that agree with the label sequence. gatherConstraints(InstanceList) - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood gatherConstraints(PRAuxiliaryModel, double[][][][]) - Method in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL gatherExpectationsOrConstraints(boolean) - Method in class cc.mallet.fst.MEMMTrainer.MEMMOptimizableByLabelLikelihood gaussianPrior(double) - Method in class cc.mallet.fst.CRF.Factors Return the log(p(parameters)) according to a zero-mean Gaussian with given variance. gaussianPriorVariance - Variable in class cc.mallet.classify.MaxEntOptimizableByGE gaussianPriorVariance - Variable in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL GEConstraint - Interface in cc.mallet.fst.semi_supervised.constraints Interface for GE constraint that considers either one or two states. GELattice - Class in cc.mallet.fst.semi_supervised Runs the dynamic programming algorithm of [Mann and McCallum 08] for computing the gradient of a Generalized Expectation constraint that considers a single label of a linear chain CRF. GELattice(FeatureVectorSequence, double[][], double[][][], Transducer, int[][], int[][], CRF.Factors, ArrayList<GEConstraint>, boolean) - Constructor for class cc.mallet.fst.semi_supervised.GELattice GELattice.LatticeNode - Class in cc.mallet.fst.semi_supervised Contains forward-backward vectors correspoding to an input position and a state index. GELattice.LatticeNode() - Constructor for class cc.mallet.fst.semi_supervised.GELattice.LatticeNode GeneralUtils - Class in cc.mallet.grmm.util Static utility methods that didn't seem to belong anywhere else. generateAttractivePotentialValues(Random, double) - Static method in class cc.mallet.grmm.inference.RandomGraphs generateMixedPotentialValues(Random, double) - Static method in class cc.mallet.grmm.inference.RandomGraphs generatePath() - Method in class cc.mallet.fst.Transducer generateStoplist(SimpleTokenizer) - Static method in class cc.mallet.util.BulkLoader Read the data from inputFile, then write all the words that do not occur pruneCount.value times or more to the pruned word file. GenericAcrfData2TokenSequence - Class in cc.mallet.grmm.learning Generic pipe that takes a linegroup of the form: GenericAcrfData2TokenSequence() - Constructor for class cc.mallet.grmm.learning.GenericAcrfData2TokenSequence GenericAcrfData2TokenSequence(int) - Constructor for class cc.mallet.grmm.learning.GenericAcrfData2TokenSequence GenericAcrfTui - Class in cc.mallet.grmm.learning GenericAcrfTui() - Constructor for class cc.mallet.grmm.learning.GenericAcrfTui get(int) - Method in class cc.mallet.cluster.Clusterings get(int, int) - Method in class cc.mallet.cluster.util.PairwiseMatrix get(Object, Object) - Method in class cc.mallet.grmm.inference.MessageArray get(Variable, Factor) - Method in class cc.mallet.grmm.inference.MessageArray get(Factor, Variable) - Method in class cc.mallet.grmm.inference.MessageArray get(int) - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph get(Variable) - Method in class cc.mallet.grmm.types.Assignment get(int, Variable) - Method in class cc.mallet.grmm.types.Assignment Returns the value of var in this assigment. get(int) - Method in class cc.mallet.grmm.types.BitVarSet get(int) - Method in class cc.mallet.grmm.types.FactorGraph Returns a variable from this model with a given index. get(int) - Method in class cc.mallet.grmm.types.HashVarSet get(int) - Method in class cc.mallet.grmm.types.ListVarSet get(int, int) - Method in class cc.mallet.grmm.types.UndirectedGrid get(int) - Method in class cc.mallet.grmm.types.Universe get(int) - Method in class cc.mallet.grmm.types.UnmodifiableVarSet get(int) - Method in interface cc.mallet.grmm.types.VarSet Returns the variable in this clique at index idx. get(int, int) - Method in class cc.mallet.grmm.util.CSIntInt2ObjectMultiMap get(int, int) - Method in class cc.mallet.grmm.util.MIntInt2ObjectMap get(Object) - Method in class cc.mallet.grmm.util.THashMultiMap get(int) - Method in class cc.mallet.types.ArraySequence get(int) - Method in class cc.mallet.types.FeatureConjunction.List get(int) - Method in class cc.mallet.types.FeatureCounter get(Object) - Method in class cc.mallet.types.FeatureCounter Unlike increment(Object), this method does not add the entry to the Alphabet if it is not there already. get(int) - Method in class cc.mallet.types.FeatureSequence get(int) - Method in class cc.mallet.types.FeatureVectorSequence get(int) - Method in class cc.mallet.types.Labels get(int) - Method in class cc.mallet.types.LabelsSequence get(int) - Method in class cc.mallet.types.MultiInstanceList get(int) - Method in class cc.mallet.types.PagedInstanceList Returns the Instance at the specified index. get(int) - Method in interface cc.mallet.types.Sequence get(int) - Method in class cc.mallet.util.DoubleList getAccuracy(InstanceList) - Method in class cc.mallet.classify.Classifier getAccuracy() - Method in class cc.mallet.classify.Trial Return the fraction of instances that have the correct label as their best predicted label. getAccuracy(String) - Method in class cc.mallet.fst.InstanceAccuracyEvaluator getAccuracy(String) - Method in class cc.mallet.fst.TokenAccuracyEvaluator Returns the accuracy from the last time test() or evaluate() was called getAccuracyCoverageValues() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator get accuracy at coverage for each bin of values getAccuracyRecallValues(int) - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator get accuracy at recall for each bin of values getAcrf() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor getAdjacentVertices(Variable) - Method in class cc.mallet.grmm.types.FactorGraph Returns all variables that are adjacent to a given variable in this graph---that is, the set of all variables that share a factor with this one. getAlpha(int, int, int) - Method in class cc.mallet.fst.semi_supervised.GELattice getAlpha(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getAlpha(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getAlpha(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getAlpha(int, Transducer.State) - Method in interface cc.mallet.fst.SumLattice getAlpha(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeBeam getAlpha(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeDefault getAlpha(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeScaling getAlphabet() - Method in class cc.mallet.classify.Classifier getAlphabet() - Method in class cc.mallet.classify.NaiveBayesTrainer getAlphabet() - Method in class cc.mallet.grmm.util.LabelsAssignment getAlphabet() - Method in class cc.mallet.pipe.iterator.RandomFeatureVectorIterator getAlphabet() - Method in class cc.mallet.pipe.iterator.RandomTokenSequenceIterator getAlphabet() - Method in class cc.mallet.pipe.Pipe getAlphabet() - Method in class cc.mallet.topics.LDAHyper Deprecated. getAlphabet() - Method in class cc.mallet.topics.ParallelTopicModel getAlphabet() - Method in class cc.mallet.topics.SimpleLDA getAlphabet() - Method in interface cc.mallet.types.AlphabetCarrying getAlphabet() - Method in class cc.mallet.types.Dirichlet getAlphabet() - Method in class cc.mallet.types.FeatureSelection getAlphabet() - Method in class cc.mallet.types.FeatureSequence getAlphabet() - Method in class cc.mallet.types.FeatureVector getAlphabet() - Method in class cc.mallet.types.FeatureVectorSequence getAlphabet() - Method in class cc.mallet.types.Instance getAlphabet() - Method in class cc.mallet.types.InstanceList getAlphabet() - Method in class cc.mallet.types.Label getAlphabet() - Method in class cc.mallet.types.Labelings getAlphabet() - Method in class cc.mallet.types.Labels getAlphabet() - Method in class cc.mallet.types.LabelsSequence getAlphabet() - Method in class cc.mallet.types.Multinomial getAlphabet() - Method in class cc.mallet.types.NullLabel getAlphabet() - Method in class cc.mallet.types.ROCData getAlphabets() - Method in class cc.mallet.classify.Classifier getAlphabets() - Method in class cc.mallet.classify.NaiveBayesTrainer getAlphabets() - Method in class cc.mallet.grmm.util.LabelsAssignment getAlphabets() - Method in class cc.mallet.pipe.Pipe getAlphabets() - Method in interface cc.mallet.types.AlphabetCarrying getAlphabets() - Method in class cc.mallet.types.FeatureSelection getAlphabets() - Method in class cc.mallet.types.FeatureSequence getAlphabets() - Method in class cc.mallet.types.FeatureVector getAlphabets() - Method in class cc.mallet.types.FeatureVectorSequence getAlphabets() - Method in class cc.mallet.types.Instance getAlphabets() - Method in class cc.mallet.types.InstanceList getAlphabets() - Method in class cc.mallet.types.Label getAlphabets() - Method in class cc.mallet.types.Labelings getAlphabets() - Method in class cc.mallet.types.Labels getAlphabets() - Method in class cc.mallet.types.LabelsSequence getAlphabets() - Method in class cc.mallet.types.NullLabel getAlphabets() - Method in class cc.mallet.types.ROCData getAssignment() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph Returns an Assignment object that corresponds to the LabelSequence for which this graph was unrolled. getAssignmentsPresent() - Method in class cc.mallet.grmm.learning.ACRF.Template getAuxiliaryValueContribution(double[]) - Method in class cc.mallet.classify.constraints.pr.MaxEntL2FLPRConstraints getAuxiliaryValueContribution(double[]) - Method in interface cc.mallet.classify.constraints.pr.MaxEntPRConstraint getAuxiliaryValueContribution(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints getAuxiliaryValueContribution(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints getAuxiliaryValueContribution(double[]) - Method in interface cc.mallet.fst.semi_supervised.pr.constraints.PRConstraint getAuxModel() - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getAverageAccuracy() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator getAverageCorrectConfidence() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator Average confidence score for the incorrect entities getAverageIncorrectConfidence() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator Average confidence score for the incorrect entities getAveragePrecision() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator IR Average precision measure. getAverageRank(InstanceList) - Method in class cc.mallet.classify.Classifier getAverageRank() - Method in class cc.mallet.classify.Trial Return the average rank of the correct class label as returned by Labeling.getRank(correctLabel) on the predicted Labeling. getBackgroundTag() - Method in class cc.mallet.extract.CRFExtractor getBackgroundTag() - Method in class cc.mallet.extract.DocumentExtraction getBaseEntropy() - Method in class cc.mallet.types.GainRatio getBaseEntropy() - Method in class cc.mallet.types.InfoGain getBaseLabelDistribution() - Method in class cc.mallet.types.GainRatio getBaseLabelDistribution() - Method in class cc.mallet.types.InfoGain getBaseModel() - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getBatchValue(int, int[]) - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood Returns the log probability of a batch of training sequence labels and the prior over parameters, if last batch then incorporate the prior on parameters as well. getBatchValue(int, int[]) - Method in class cc.mallet.grmm.util.CachingOptimizable.ByBatchGradient getBatchValue(int, int[]) - Method in interface cc.mallet.optimize.Optimizable.ByBatchGradient getBatchValue(int, int[]) - Method in interface cc.mallet.optimize.Optimizable.ByCombiningBatchGradient getBatchValueGradient(double[], int, int[]) - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getBatchValueGradient(double[], int, int[]) - Method in class cc.mallet.grmm.util.CachingOptimizable.ByBatchGradient getBatchValueGradient(double[], int, int[]) - Method in interface cc.mallet.optimize.Optimizable.ByBatchGradient getBatchValueGradient(double[], int, int[]) - Method in interface cc.mallet.optimize.Optimizable.ByCombiningBatchGradient getBeamWidth() - Method in class cc.mallet.fst.SumLatticeBeam getBestIndex() - Method in class cc.mallet.types.Label getBestIndex() - Method in interface cc.mallet.types.Labeling getBestIndex() - Method in class cc.mallet.types.LabelVector getBestLabel() - Method in class cc.mallet.types.Label getBestLabel() - Method in interface cc.mallet.types.Labeling getBestLabel() - Method in class cc.mallet.types.LabelVector getBestLabels(InstanceList) - Method in class cc.mallet.grmm.learning.ACRF getBestLabels(Instance) - Method in class cc.mallet.grmm.learning.ACRF getBestValue() - Method in class cc.mallet.types.Label getBestValue() - Method in interface cc.mallet.types.Labeling getBestValue() - Method in class cc.mallet.types.LabelVector getBeta(int, int, int) - Method in class cc.mallet.fst.semi_supervised.GELattice getBeta(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getBeta(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getBeta(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getBeta(int, Transducer.State) - Method in interface cc.mallet.fst.SumLattice getBeta(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeBeam getBeta(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeDefault getBeta(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeScaling getBiAlphabet() - Method in class cc.mallet.types.FeatureSequenceWithBigrams getBigramAlphabet() - Method in class cc.mallet.pipe.TokenSequence2FeatureSequenceWithBigrams getBiIndexAtPosition(int) - Method in class cc.mallet.types.FeatureSequenceWithBigrams getBitSet() - Method in class cc.mallet.types.FeatureSelection getCachedDots() - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getCachedGradient(double[]) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable getCharSequence() - Method in class cc.mallet.util.CharSequenceLexer getChild() - Method in class cc.mallet.grmm.types.CPT getChildren(Object) - Method in class cc.mallet.grmm.types.Tree getClassificationProbs(Instance, double[]) - Method in class cc.mallet.classify.PRAuxClassifier getClassificationScores(Instance, double[]) - Method in class cc.mallet.classify.MaxEnt getClassificationScores(Instance, double[]) - Method in class cc.mallet.classify.MCMaxEnt getClassificationScores(Instance, double[]) - Method in class cc.mallet.classify.PRAuxClassifier getClassificationScores(Instance, double[]) - Method in class cc.mallet.classify.RankMaxEnt getClassificationScoresForTies(Instance, double[], int[]) - Method in class cc.mallet.classify.RankMaxEnt Used by RankMaxEntTrainer to calculate the value when the labeling contains ties. getClassificationScoresWithTemperature(Instance, double, double[]) - Method in class cc.mallet.classify.MaxEnt getClassifier() - Method in class cc.mallet.classify.AdaBoostM2Trainer getClassifier() - Method in class cc.mallet.classify.AdaBoostTrainer getClassifier() - Method in class cc.mallet.classify.BaggingTrainer getClassifier() - Method in class cc.mallet.classify.BalancedWinnowTrainer getClassifier() - Method in class cc.mallet.classify.C45Trainer getClassifier() - Method in class cc.mallet.classify.Classification getClassifier() - Method in class cc.mallet.classify.ClassifierEnsembleTrainer getClassifier() - Method in class cc.mallet.classify.ClassifierTrainer getClassifier() - Method in class cc.mallet.classify.ConfidencePredictingClassifierTrainer getClassifier() - Method in class cc.mallet.classify.DecisionTreeTrainer getClassifier() - Method in class cc.mallet.classify.FeatureSelectingClassifierTrainer getClassifier() - Method in class cc.mallet.classify.MaxEntGERangeTrainer getClassifier() - Method in class cc.mallet.classify.MaxEntGETrainer getClassifier() - Method in class cc.mallet.classify.MaxEntOptimizableByGE getClassifier() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution getClassifier() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood getClassifier() - Method in class cc.mallet.classify.MaxEntPRTrainer getClassifier() - Method in class cc.mallet.classify.MaxEntTrainer getClassifier() - Method in class cc.mallet.classify.MCMaxEntTrainer getClassifier() - Method in class cc.mallet.classify.NaiveBayesEMTrainer getClassifier() - Method in class cc.mallet.classify.NaiveBayesTrainer getClassifier() - Method in class cc.mallet.classify.Trial getClassifier() - Method in class cc.mallet.classify.WinnowTrainer getClassifier() - Method in class cc.mallet.cluster.neighbor_evaluator.ClassifyingNeighborEvaluator getClassifier() - Method in class cc.mallet.fst.confidence.MaxEntSequenceConfidenceEstimator getClassifier() - Method in class cc.mallet.topics.DMROptimizable getClassPrior(int) - Method in class cc.mallet.classify.evaluate.ConfusionMatrix Returns the percentage of instances with true label = classIndex getCluster(int) - Method in class cc.mallet.cluster.Clustering Return an list of instances with a particular label. getClustering() - Method in class cc.mallet.cluster.iterator.NeighborIterator getClusterMeans() - Method in class cc.mallet.cluster.KMeans Return the ArrayList of cluster means after a run of the algorithm. getClusters() - Method in class cc.mallet.cluster.Clustering Returns an array of instance lists corresponding to clusters. getCodocumentMatrix(int) - Method in class cc.mallet.topics.TopicModelDiagnostics getCoherence() - Method in class cc.mallet.topics.TopicModelDiagnostics getCollectGarbage() - Method in class cc.mallet.types.PagedInstanceList getColumnInt(Variable) - Method in class cc.mallet.grmm.types.Assignment getCombinedInstances(Clustering, int, int) - Static method in class cc.mallet.cluster.util.ClusterUtils getCommandOption(int) - Method in class cc.mallet.util.CommandOption.List getCommandOptionList() - Static method in class cc.mallet.classify.MCMaxEntTrainer getCommandOptionList() - Method in interface cc.mallet.util.CommandOption.ListProviding getComparator() - Method in class cc.mallet.extract.AccuracyCoverageEvaluator getComparator() - Method in class cc.mallet.extract.PerDocumentF1Evaluator getComparator() - Method in class cc.mallet.extract.PerFieldF1Evaluator getCompleteValueContrib() - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint getCompleteValueContribution() - Method in class cc.mallet.classify.constraints.pr.MaxEntL2FLPRConstraints getCompleteValueContribution() - Method in interface cc.mallet.classify.constraints.pr.MaxEntPRConstraint getCompleteValueContribution(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints getCompleteValueContribution(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints getCompleteValueContribution(double[]) - Method in interface cc.mallet.fst.semi_supervised.pr.constraints.PRConstraint getCompleteValueContribution() - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getCompleteValueContribution() - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getCompositeConstraintFeatureValue(FeatureVector, int) - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints getCompositeConstraintFeatureValue(FeatureVector, int) - Method in interface cc.mallet.classify.constraints.ge.MaxEntGEConstraint Computes the composite constraint feature value (over all constraint features) for FeatureVector fv and label label. getCompositeConstraintFeatureValue(FeatureVector, int) - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints getCompositeConstraintFeatureValue(FeatureVector, int, int, int) - Method in interface cc.mallet.fst.semi_supervised.constraints.GEConstraint Computes the composite constraint feature value (over all constraint features) for FeatureVector fv and a transition from state li1 to li2. getCompositeConstraintFeatureValue(FeatureVector, int, int, int) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints getCompositeConstraintFeatureValue(FeatureVector, int, int, int) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints getCompositeConstraintFeatureValue(FeatureVector, int, int, int) - Method in class cc.mallet.fst.semi_supervised.constraints.SelfTransitionGEConstraint getCompositeConstraintFeatureValue(FeatureVector, int, int, int) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints getConfidence() - Method in class cc.mallet.extract.LabeledSpan getConfidence() - Method in class cc.mallet.fst.confidence.InstanceWithConfidence getConfidence() - Method in class cc.mallet.fst.confidence.PipedInstanceWithConfidence getConfidence() - Method in class cc.mallet.fst.Segment getConfidenceMean() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator getConfidenceStandardDeviation() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator Standard deviation of confidence scores getConfidenceSum() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator getConfusionBetween(int, int) - Method in class cc.mallet.classify.evaluate.ConfusionMatrix Returns percent of time that class2 is true class when class1 is predicted class getConstraint(int) - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getConstraintFeatures() - Method in class cc.mallet.classify.PRAuxClassifier getConstraints(int) - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF getConstraints(int) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable getConstraints(int) - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable getConstraints(int) - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable getCost() - Method in class cc.mallet.util.search.SearchNode Get the cost for this node. getCount() - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints.MaxEntFLGEConstraint getCount() - Method in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints.MaxEntFLPRConstraint getCount() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints.OneLabelGEConstraint getCount(int) - Method in class cc.mallet.types.Multinomial.Estimator getCountFeatureTopic(int, int) - Method in class cc.mallet.topics.LDAHyper Deprecated. getCounts(Label) - Method in class cc.mallet.types.ROCData Gets the raw counts for a specified label. getCounts(Label, double) - Method in class cc.mallet.types.ROCData Gets the raw counts for a specified label and threshold. getCountTokensPerTopic(int) - Method in class cc.mallet.topics.LDAHyper Deprecated. getCountWithFeature(int) - Method in class cc.mallet.types.InvertedIndex getCountWithFeature(Object) - Method in class cc.mallet.types.InvertedIndex getCPF(VarSet) - Method in class cc.mallet.grmm.inference.JunctionTree getCptofVar(Variable) - Method in class cc.mallet.grmm.types.DirectedModel Returns the conditional distribution P ( node | Parents (node) ) getCrf() - Method in class cc.mallet.extract.CRFExtractor getCRF() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getCRF() - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getCRF() - Method in class cc.mallet.fst.CRFTrainerByValueGradients getCRF(InstanceList, int[], String, String, String, boolean) - Static method in class cc.mallet.fst.semi_supervised.tui.SimpleTaggerWithConstraints getData() - Method in class cc.mallet.topics.LDAHyper Deprecated. getData() - Method in class cc.mallet.topics.ParallelTopicModel getData() - Method in class cc.mallet.topics.PolylingualTopicModel getData() - Method in class cc.mallet.topics.SimpleLDA getData() - Method in class cc.mallet.types.Instance getData() - Method in class cc.mallet.util.Univariate getDataAlphabet() - Method in class cc.mallet.pipe.AddClassifierTokenPredictions getDataAlphabet() - Method in class cc.mallet.pipe.Pipe getDataAlphabet() - Method in class cc.mallet.types.Instance getDataAlphabet() - Method in class cc.mallet.types.InstanceList Returns the Alphabet mapping features of the data to integers. getDataClass() - Method in class cc.mallet.types.InstanceList Returns the Java Class 'data' field of Instances in this list. getDefaultFeatureIndex() - Method in class cc.mallet.classify.MaxEnt getDefaultFeatureIndex() - Method in class cc.mallet.grmm.learning.ACRF getDefaultWeight(int) - Method in class cc.mallet.grmm.learning.ACRF.Template getDefaultWeights() - Method in class cc.mallet.fst.CRF getDefaultWeights() - Method in class cc.mallet.grmm.learning.ACRF.FixedFactorTemplate getDefaultWeights() - Method in class cc.mallet.grmm.learning.ACRF.Template getDegree(Variable) - Method in class cc.mallet.grmm.types.FactorGraph Returns the degree of a given variable in this factor graph, that is, the number of factors in which the variable is an argument. getDelta(int, int) - Method in interface cc.mallet.fst.MaxLattice getDelta(int, int) - Method in class cc.mallet.fst.MaxLatticeDefault getDepthLimited() - Method in class cc.mallet.classify.C45Trainer getDestinationState(int) - Method in class cc.mallet.fst.CRF.State getDestinationState() - Method in class cc.mallet.fst.CRF.TransitionIterator getDestinationState() - Method in class cc.mallet.fst.FeatureTransducer.Transition getDestinationState() - Method in class cc.mallet.fst.FeatureTransducer.TransitionIterator getDestinationState(int) - Method in class cc.mallet.fst.HMM.State getDestinationState() - Method in class cc.mallet.fst.HMM.TransitionIterator getDestinationState() - Method in class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator getDestinationState() - Method in class cc.mallet.fst.Transducer.TransitionIterator The state we are in after taking this transition. getDimensions(int[]) - Method in interface cc.mallet.types.ConstantMatrix getDimensions(int[]) - Method in class cc.mallet.types.DenseMatrix getDimensions(int[]) - Method in class cc.mallet.types.DenseVector getDimensions(int[]) - Method in class cc.mallet.types.Matrix2 Deprecated. getDimensions(int[]) - Method in class cc.mallet.types.Matrixn getDimensions(int[]) - Method in class cc.mallet.types.SparseMatrixn getDimensions(int[]) - Method in class cc.mallet.types.SparseVector getDistanceFromCorpus() - Method in class cc.mallet.topics.TopicModelDiagnostics Low-quality topics may be very similar to the global distribution. getDistanceFromUniform() - Method in class cc.mallet.topics.TopicModelDiagnostics getDocLengthCounts() - Method in class cc.mallet.topics.WorkerRunnable getDocLengthNormalization() - Method in class cc.mallet.classify.NaiveBayesEMTrainer getDocLengthNormalization() - Method in class cc.mallet.classify.NaiveBayesTrainer getDocTopicCounts() - Method in class cc.mallet.topics.LDA Deprecated. getDocument() - Method in class cc.mallet.extract.DocumentExtraction getDocument() - Method in class cc.mallet.extract.LabeledSpan getDocument() - Method in class cc.mallet.extract.LabeledSpans getDocument() - Method in interface cc.mallet.extract.Span getDocument() - Method in class cc.mallet.extract.StringSpan getDocument() - Method in class cc.mallet.extract.StringTokenization getDocument() - Method in interface cc.mallet.extract.Tokenization Returns the document of which this is a tokenization. getDocumentEntropy(int[]) - Method in class cc.mallet.topics.TopicModelDiagnostics getDocumentExtraction(int) - Method in class cc.mallet.extract.Extraction getDocumentPercent(int) - Method in class cc.mallet.topics.TopicModelDiagnostics getDocumentPercentRatio(int, int) - Method in class cc.mallet.topics.TopicModelDiagnostics getDoPruning() - Method in class cc.mallet.classify.C45Trainer getDouble(Variable) - Method in class cc.mallet.grmm.types.Assignment getDouble(int, Variable) - Method in class cc.mallet.grmm.types.Assignment Returns the value of var in this assigment. getEdgeSet() - Method in class cc.mallet.grmm.types.UndirectedModel getEffectiveNumberOfWords() - Method in class cc.mallet.topics.TopicModelDiagnostics getEnd() - Method in class cc.mallet.fst.Segment getEndIdx() - Method in class cc.mallet.extract.LabeledSpan getEndIdx() - Method in interface cc.mallet.extract.Span Returns an integer index identifying the end of this span. getEndIdx() - Method in class cc.mallet.extract.StringSpan getEndOffset() - Method in class cc.mallet.util.CharSequenceLexer getEndOffset() - Method in interface cc.mallet.util.Lexer getEntropy() - Method in class cc.mallet.fst.semi_supervised.EntropyLattice getEntropy(double[]) - Static method in class cc.mallet.util.Maths getEntry() - Method in class cc.mallet.types.Label getErrorOutputStream() - Method in class cc.mallet.extract.AccuracyCoverageEvaluator getErrorOutputStream() - Method in class cc.mallet.extract.PerDocumentF1Evaluator getErrorOutputStream() - Method in class cc.mallet.extract.PerFieldF1Evaluator getEvaluationScores(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.AccuracyEvaluator getEvaluationScores(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.BCubedEvaluator getEvaluationScores(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluator getEvaluationScores(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.ClusteringEvaluators getEvaluationScores(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.MUCEvaluator getEvaluationScores(Clustering, Clustering) - Method in class cc.mallet.cluster.evaluate.PairF1Evaluator getEvaluator() - Method in class cc.mallet.cluster.HillClimbingClusterer getExpectation() - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints.MaxEntFLGEConstraint getExpectation() - Method in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints.MaxEntFLPRConstraint getExpectation() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints.OneLabelGEConstraint getExpectations(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints getExpectations(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint getExpectations(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints getExpectations(double[]) - Method in interface cc.mallet.fst.semi_supervised.pr.constraints.PRConstraint getExpectations(int) - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF getExpectations(int) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable getExpectations(int) - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable getExpectations(int) - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable getExpectationValue(int, int[]) - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood Computes log probability of a batch of training data, fill in corresponding expectations as well getExpectationValue() - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getExpectationValue() - Method in class cc.mallet.fst.MEMMTrainer.MEMMOptimizableByLabelLikelihood getExpectationValue() - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getExpectationValue() - Method in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL getExtractedSpans() - Method in class cc.mallet.extract.DocumentExtraction getExtractor() - Method in class cc.mallet.extract.Extraction getF1(InstanceList, int) - Method in class cc.mallet.classify.Classifier getF1(InstanceList, Labeling) - Method in class cc.mallet.classify.Classifier getF1(InstanceList, Object) - Method in class cc.mallet.classify.Classifier getF1(Object) - Method in class cc.mallet.classify.Trial Calculate the F1-measure of the classifier on an instance list for a particular target entry getF1(Labeling) - Method in class cc.mallet.classify.Trial getF1(int) - Method in class cc.mallet.classify.Trial Calculate the F1-measure for a particular target index from an array list of classifications getFactor() - Method in class cc.mallet.grmm.learning.ACRF.BigramTemplate getFactor() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledVarSet getFactor(int) - Method in class cc.mallet.grmm.types.FactorGraph getFeatureAbsentChild() - Method in class cc.mallet.classify.DecisionTree.Node getFeatureIndices(Alphabet, String) - Static method in class cc.mallet.types.FeatureConjunction getFeatureLabelCounts(InstanceList, boolean) - Static method in class cc.mallet.classify.FeatureConstraintUtil getFeatureMultinomialEstimator() - Method in class cc.mallet.classify.NaiveBayesEMTrainer getFeatureMultinomialEstimator() - Method in class cc.mallet.classify.NaiveBayesTrainer Get the MultinomialEstimator instance used to specify the type of estimator for features. getFeatureName() - Method in class cc.mallet.pipe.tsf.OffsetFeatureConjunction getFeaturePatterns() - Method in class cc.mallet.pipe.tsf.OffsetFeatureConjunction getFeaturePipe() - Method in class cc.mallet.extract.CRFExtractor getFeaturePipe() - Method in interface cc.mallet.extract.Extractor Returns the pipe used by this extractor for. getFeaturePipe() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor getFeaturePresentChild() - Method in class cc.mallet.classify.DecisionTree.Node getFeatures() - Method in class cc.mallet.fst.confidence.SequenceConfidenceInstance getFeatures() - Method in class cc.mallet.types.FeatureSequence getFeatures() - Method in interface cc.mallet.types.PropertyHolder getFeatures() - Method in class cc.mallet.types.Token getFeatureSelection() - Method in class cc.mallet.classify.Classifier getFeatureSelection() - Method in class cc.mallet.classify.MaxEnt getFeatureSelection() - Method in class cc.mallet.types.InstanceList getFeaturesIncludeToken() - Method in class cc.mallet.grmm.learning.GenericAcrfData2TokenSequence getFeatureValue(String) - Method in class cc.mallet.fst.confidence.SequenceConfidenceInstance getFeatureValue(String) - Method in interface cc.mallet.types.PropertyHolder getFeatureValue(String) - Method in class cc.mallet.types.Token getFeatureVector(int) - Method in class cc.mallet.types.FeatureVectorSequence getField(Label) - Method in class cc.mallet.extract.Record getFileArray() - Method in class cc.mallet.pipe.iterator.FileIterator getFileArray() - Method in class cc.mallet.pipe.iterator.FileListIterator getFileArray() - Method in class cc.mallet.pipe.iterator.UnlabeledFileIterator getFilter() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer getFinalWeight() - Method in class cc.mallet.fst.CRF.State getFinalWeight() - Method in class cc.mallet.fst.FeatureTransducer.State getFinalWeight() - Method in class cc.mallet.fst.HMM.State getFinalWeight() - Method in class cc.mallet.fst.Transducer.State getFirstString() - Method in class cc.mallet.types.StringEditVector getFirstStringChar(int) - Method in class cc.mallet.types.StringEditVector getFixedTemplates() - Method in class cc.mallet.grmm.learning.ACRF getFlops() - Static method in class cc.mallet.grmm.util.Flops getFullName() - Method in class cc.mallet.util.CommandOption getFv() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledVarSet getGainRatio() - Method in class cc.mallet.classify.C45.Node getGammaProbability(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getGammaProbability(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getGammaProbability(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getGammaProbability(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getGammaProbability(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getGammaProbability(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getGammaProbability(int, Transducer.State) - Method in interface cc.mallet.fst.SumLattice getGammaProbability(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeBeam getGammaProbability(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeDefault getGammaProbability(int, int) - Method in class cc.mallet.fst.SumLatticeDefault getGammaProbability(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeScaling getGammaProbability(int, int) - Method in class cc.mallet.fst.SumLatticeScaling getGammas() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getGammas() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getGammas() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getGammas() - Method in interface cc.mallet.fst.SumLattice getGammas() - Method in class cc.mallet.fst.SumLatticeBeam getGammas() - Method in class cc.mallet.fst.SumLatticeDefault getGammas() - Method in class cc.mallet.fst.SumLatticeScaling getGammaWeight(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getGammaWeight(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getGammaWeight(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getGammaWeight(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getGammaWeight(int, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getGammaWeight(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getGammaWeight(int, Transducer.State) - Method in interface cc.mallet.fst.SumLattice getGammaWeight(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeBeam getGammaWeight(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeDefault getGammaWeight(int, int) - Method in class cc.mallet.fst.SumLatticeDefault getGammaWeight(int, Transducer.State) - Method in class cc.mallet.fst.SumLatticeScaling getGammaWeight(int, int) - Method in class cc.mallet.fst.SumLatticeScaling getGaussianPriorVariance() - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getGaussianPriorVariance() - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getGaussianPriorVariance() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getGaussianPriorVariance() - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getGaussianPriorVariance() - Method in class cc.mallet.grmm.learning.ACRF getGaussianPriorVariance() - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable getGaussianPriorVariance() - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable getGaussianPriorVariance() - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable getGISUpdate(double[]) - Method in interface cc.mallet.optimize.Optimizable.ByGISUpdate getGradient(double[], double[]) - Method in class cc.mallet.classify.constraints.pr.MaxEntL2FLPRConstraints getGradient(double[], double[]) - Method in interface cc.mallet.classify.constraints.pr.MaxEntPRConstraint getGradient(double[], double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints getGradient(double[], double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint getGradient(double[], double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints getGradient(double[], double[]) - Method in interface cc.mallet.fst.semi_supervised.pr.constraints.PRConstraint getGradientContribution(int) - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints.MaxEntL2IndGEConstraint getGradientContribution(int) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints.OneLabelL2IndGEConstraint getHeight() - Method in class cc.mallet.grmm.types.UndirectedGrid getID() - Method in class cc.mallet.types.IDSorter getIndex() - Method in class cc.mallet.fst.CRF.State getIndex() - Method in class cc.mallet.fst.CRF.TransitionIterator getIndex() - Method in class cc.mallet.fst.FeatureTransducer.State getIndex() - Method in class cc.mallet.fst.FeatureTransducer.TransitionIterator getIndex() - Method in class cc.mallet.fst.HMM.State getIndex() - Method in class cc.mallet.fst.HMM.TransitionIterator getIndex() - Method in class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator getIndex() - Method in class cc.mallet.fst.Transducer.State getIndex() - Method in class cc.mallet.fst.Transducer.TransitionIterator An implementation-specific index for this transition object, can be used to index into arrays of per-transition parameters. getIndex(Factor) - Method in class cc.mallet.grmm.inference.MessageArray getIndex(Variable) - Method in class cc.mallet.grmm.inference.MessageArray getIndex(VarSet) - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph getIndex(Variable) - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph getIndex(Variable) - Method in class cc.mallet.grmm.types.FactorGraph Returns a unique numeric index for a variable in this model. getIndex(Factor) - Method in class cc.mallet.grmm.types.FactorGraph getIndex(Variable) - Method in class cc.mallet.grmm.types.Universe getIndex() - Method in class cc.mallet.grmm.types.Variable Returns the index of this variable in its universe getIndex() - Method in class cc.mallet.types.FeatureConjunction getIndex() - Method in class cc.mallet.types.FeatureVectorSequence.Iterator getIndex() - Method in class cc.mallet.types.Label getIndex() - Method in class cc.mallet.types.LabelSequence.Iterator getIndexAtPosition(int) - Method in class cc.mallet.types.FeatureSequence getIndexAtRank(int) - Method in class cc.mallet.types.RankedFeatureVector getIndices() - Method in class cc.mallet.types.SparseMatrixn Returns an array of all the present indices. getIndices() - Method in class cc.mallet.types.SparseVector getIndicesWithLabel(int) - Method in class cc.mallet.cluster.Clustering getInertiaWeight() - Method in class cc.mallet.grmm.inference.gbp.ParentChildGBP getInferenceCache(Class) - Method in class cc.mallet.grmm.types.FactorGraph Caches some information about this graph that is specific to a given type of inferencer (e.g., a junction tree). getInferencer() - Method in class cc.mallet.grmm.learning.ACRF getInferencer() - Method in class cc.mallet.topics.ParallelTopicModel Return a tool for estimating topic distributions for new documents getInferencer(int) - Method in class cc.mallet.topics.PolylingualTopicModel Return a tool for estimating topic distributions for new documents getInfoGain(int) - Method in class cc.mallet.types.PerLabelInfoGain getInitialStepSize() - Method in class cc.mallet.optimize.ConjugateGradient getInitialStepSize() - Method in class cc.mallet.optimize.GradientAscent getInitialWeight() - Method in class cc.mallet.fst.CRF.State getInitialWeight() - Method in class cc.mallet.fst.FeatureTransducer.State getInitialWeight() - Method in class cc.mallet.fst.HMM.State getInitialWeight() - Method in class cc.mallet.fst.Transducer.State getInProduction() - Method in class cc.mallet.pipe.AddClassifierTokenPredictions getInput() - Method in class cc.mallet.extract.DocumentExtraction getInput() - Method in class cc.mallet.fst.CRF.TransitionIterator getInput() - Method in class cc.mallet.fst.FeatureTransducer.TransitionIterator getInput() - Method in class cc.mallet.fst.HMM.TransitionIterator getInput() - Method in class cc.mallet.fst.MaxLatticeDefault getInput() - Method in class cc.mallet.fst.Segment getInput() - Method in class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator getInput() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getInput() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getInput() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getInput() - Method in interface cc.mallet.fst.SumLattice getInput() - Method in class cc.mallet.fst.SumLatticeBeam getInput() - Method in class cc.mallet.fst.SumLatticeDefault getInput() - Method in class cc.mallet.fst.SumLatticeScaling getInput() - Method in class cc.mallet.fst.Transducer.TransitionIterator The input symbol or object appearing on this transition. getInputAlphabet() - Method in class cc.mallet.extract.CRFExtractor getInputAlphabet() - Method in interface cc.mallet.extract.Extractor Returns an alphabet of the features used by the extractor. getInputAlphabet() - Method in class cc.mallet.fst.CRF getInputAlphabet() - Method in class cc.mallet.fst.FeatureTransducer getInputAlphabet() - Method in class cc.mallet.fst.HMM getInputAlphabet() - Method in class cc.mallet.grmm.learning.ACRF getInputAlphabet() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor getInputPipe() - Method in class cc.mallet.fst.Transducer getInputPipe() - Method in class cc.mallet.grmm.learning.ACRF getInputPositionIncrement() - Method in class cc.mallet.fst.Transducer.TransitionIterator The number of input positions that this transition consumes. getInstance() - Method in class cc.mallet.classify.Classification getInstance() - Method in class cc.mallet.fst.confidence.InstanceWithConfidence getInstance() - Method in class cc.mallet.fst.confidence.PipedInstanceWithConfidence getInstance() - Method in class cc.mallet.fst.confidence.SequenceConfidenceInstance getInstanceId() - Method in class cc.mallet.pipe.Pipe getInstanceId() - Method in class cc.mallet.types.Alphabet getInstanceList() - Method in class cc.mallet.topics.LDA Deprecated. getInstanceList() - Method in class cc.mallet.types.InvertedIndex getInstancePipe() - Method in class cc.mallet.classify.Classifier getInstances() - Method in class cc.mallet.classify.C45.Node getInstances() - Method in class cc.mallet.cluster.Clustering getInstancesWithFeature(int) - Method in class cc.mallet.types.InvertedIndex getInstancesWithFeature(Object) - Method in class cc.mallet.types.InvertedIndex getInstanceWeight(Instance) - Method in class cc.mallet.types.InstanceList getInstanceWeight(int) - Method in class cc.mallet.types.InstanceList getInTag() - Method in class cc.mallet.fst.Segment getInterpreter() - Static method in class cc.mallet.util.CommandOption getIteration() - Method in interface cc.mallet.classify.ClassifierTrainer.ByOptimization getIteration() - Method in class cc.mallet.classify.MaxEntGERangeTrainer getIteration() - Method in class cc.mallet.classify.MaxEntGETrainer getIteration() - Method in class cc.mallet.classify.MaxEntPRTrainer getIteration() - Method in class cc.mallet.classify.MaxEntTrainer getIteration() - Method in class cc.mallet.classify.NaiveBayesEMTrainer getIteration() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getIteration() - Method in class cc.mallet.fst.CRFTrainerByStochasticGradient getIteration() - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getIteration() - Method in class cc.mallet.fst.CRFTrainerByValueGradients getIteration() - Method in class cc.mallet.fst.HMMTrainerByLikelihood getIteration() - Method in class cc.mallet.fst.MEMMTrainer getIteration() - Method in class cc.mallet.fst.NoopTransducerTrainer getIteration() - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByEntropyRegularization getIteration() - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByGE getIteration() - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByLikelihoodAndGE getIteration() - Method in class cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR getIteration() - Method in class cc.mallet.fst.ShallowTransducerTrainer Deprecated. getIteration() - Method in class cc.mallet.fst.TransducerTrainer getIteration() - Method in class cc.mallet.optimize.LimitedMemoryBFGS getIteration() - Method in class cc.mallet.optimize.OrthantWiseLimitedMemoryBFGS getJointAccuracy() - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer.LogEvaluator getJointAccuracy() - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer.TestResults getKey() - Method in class cc.mallet.util.PropertyList.Iterator getLabel(int) - Method in class cc.mallet.cluster.Clustering Get the cluster label for a particular instance. getLabel() - Method in class cc.mallet.extract.LabeledSpan getLabel(int) - Method in class cc.mallet.extract.LabeledSpans getLabel() - Method in class cc.mallet.grmm.types.BitVarSet getLabel() - Method in class cc.mallet.grmm.types.HashVarSet getLabel() - Method in class cc.mallet.grmm.types.Variable getLabelAlphabet() - Method in class cc.mallet.classify.Classifier getLabelAlphabet() - Method in class cc.mallet.extract.Extraction getLabelAlphabet() - Method in class cc.mallet.fst.semi_supervised.StateLabelMap Returns the label (target) alphabet. getLabelAlphabet(int) - Method in class cc.mallet.grmm.learning.GenericAcrfData2TokenSequence getLabelAlphabet() - Method in class cc.mallet.grmm.types.Variable getLabelAlphabet() - Method in class cc.mallet.pipe.iterator.RandomFeatureVectorIterator getLabelAlphabet() - Method in class cc.mallet.types.Label getLabelAlphabet() - Method in interface cc.mallet.types.Labeling getLabelAlphabet() - Method in class cc.mallet.types.LabelSequence getLabelAlphabet() - Method in class cc.mallet.types.LabelVector getLabelAlphabet() - Method in class cc.mallet.types.ROCData Gets the label alphabet getLabelAtPosition(int) - Method in class cc.mallet.types.LabelSequence getLabelAtRank(int) - Method in class cc.mallet.types.Label getLabelAtRank(int) - Method in interface cc.mallet.types.Labeling getLabelAtRank(int) - Method in class cc.mallet.types.LabelVector getLabeledSpan(int) - Method in class cc.mallet.extract.LabeledSpans getLabelIndex(int) - Method in class cc.mallet.fst.semi_supervised.StateLabelMap Returns the label index mapped to the state index. getLabeling() - Method in class cc.mallet.classify.Classification getLabeling() - Method in class cc.mallet.types.Instance getLabelingAtPosition(int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getLabelingAtPosition(int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getLabelingAtPosition(int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getLabelingAtPosition(int) - Method in interface cc.mallet.fst.SumLattice getLabelingAtPosition(int) - Method in class cc.mallet.fst.SumLatticeBeam getLabelingAtPosition(int) - Method in class cc.mallet.fst.SumLatticeDefault getLabelingAtPosition(int) - Method in class cc.mallet.fst.SumLatticeScaling getLabelName(int) - Method in class cc.mallet.fst.CRF.State getLabels() - Method in class cc.mallet.cluster.Clustering getLabels(int) - Method in class cc.mallet.types.LabelsSequence getLabelsSequence() - Method in class cc.mallet.grmm.util.LabelsAssignment getLabelVector() - Method in class cc.mallet.classify.Classification getLastChange() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledVarSet getLastResids() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph getLatticeNode(int, int) - Method in class cc.mallet.fst.semi_supervised.EntropyLattice getLatticeNode(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getLatticeNode(int, int) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getLatticeNode(int, int) - Method in class cc.mallet.fst.SumLatticeDefault getLatticeNode(int, int) - Method in class cc.mallet.fst.SumLatticeScaling getLearningRate() - Method in class cc.mallet.fst.CRFTrainerByStochasticGradient getLeastConfidentSegments() - Method in class cc.mallet.fst.confidence.ConstrainedViterbiTransducerCorrector Returns the least confident segments from each sequence in the previous call to correctLeastConfidentSegments getLeastConfidentSegments(InstanceList, Object[], Object[]) - Method in class cc.mallet.fst.confidence.ConstrainedViterbiTransducerCorrector Returns the least confident segments in ilist getLeftChild() - Method in class cc.mallet.classify.C45.Node getLength() - Method in class cc.mallet.types.FeatureSequence getLengthFirstString() - Method in class cc.mallet.types.StringEditVector getLengthSecondString() - Method in class cc.mallet.types.StringEditVector getLineMaximizer() - Method in class cc.mallet.optimize.GradientAscent getList(Class) - Static method in class cc.mallet.util.CommandOption getLogger(String) - Static method in class cc.mallet.util.MalletLogger getLogger(String) - Static method in class cc.mallet.util.MalletProgressMessageLogger getLogNumAssignments() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph getLogValueMatrix() - Method in class cc.mallet.grmm.types.AbstractTableFactor getLogValueMatrix() - Method in class cc.mallet.grmm.types.LogTableFactor getLogValueMatrix() - Method in class cc.mallet.grmm.types.TableFactor getMatch() - Method in class cc.mallet.types.StringEditVector getMaxDepth() - Method in class cc.mallet.classify.C45Trainer getMaxer() - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer getMaximizable(InstanceList) - Method in class cc.mallet.grmm.learning.ACRF getMaximizableTrainer(InstanceList) - Method in class cc.mallet.classify.MCMaxEntTrainer getMaximizableTrainer(InstanceList) - Method in class cc.mallet.classify.RankMaxEntTrainer getMaxLatticeFactory() - Method in class cc.mallet.fst.Transducer getMaxValue() - Method in class cc.mallet.types.RankedFeatureVector getMaxValuedIndex() - Method in class cc.mallet.types.RankedFeatureVector getMaxValuedIndexIn(FeatureSelection) - Method in class cc.mallet.types.RankedFeatureVector getMaxValuedObject() - Method in class cc.mallet.types.RankedFeatureVector getMaxValuedObjectIn(FeatureSelection) - Method in class cc.mallet.types.RankedFeatureVector getMaxValuedThreshold() - Method in class cc.mallet.types.GainRatio getMaxValueIn(FeatureSelection) - Method in class cc.mallet.types.RankedFeatureVector getMDL() - Method in class cc.mallet.classify.C45.Node Calculates the minimum description length of this node, i.e., the length of the binary encoding that describes the feature and the split value used at this node getMessager() - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation getMessagesSent() - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation Returns the total number of messages this inferencer has sent since its creation. getMessagesUsedLastTime() - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation Returns the number of messages sent during the last call to computeMarginals. getMinNumInsts() - Method in class cc.mallet.classify.C45Trainer getModified() - Method in class cc.mallet.cluster.neighbor_evaluator.Neighbor getMultinomials() - Method in class cc.mallet.classify.NaiveBayes getName() - Method in class cc.mallet.classify.C45.Node getName() - Method in class cc.mallet.classify.DecisionTree.Node getName() - Method in class cc.mallet.extract.DocumentExtraction getName() - Method in class cc.mallet.extract.Field getName() - Method in class cc.mallet.extract.Record getName() - Method in class cc.mallet.fst.CRF.State getName() - Method in class cc.mallet.fst.FeatureTransducer.State getName() - Method in class cc.mallet.fst.HMM.State getName() - Method in class cc.mallet.fst.Transducer.State getName(Alphabet, int[], boolean[]) - Static method in class cc.mallet.types.FeatureConjunction getName(Alphabet, int[]) - Static method in class cc.mallet.types.FeatureConjunction getName(Alphabet, int, int) - Static method in class cc.mallet.types.FeatureConjunction getName() - Method in class cc.mallet.types.Instance getName() - Method in class cc.mallet.util.CommandOption getNewCluster() - Method in class cc.mallet.cluster.neighbor_evaluator.AgglomerativeNeighbor getNewMessages() - Method in class cc.mallet.grmm.inference.gbp.AbstractMessageStrategy getNewMessages() - Method in interface cc.mallet.grmm.inference.gbp.MessageStrategy getNextElement() - Method in class cc.mallet.pipe.iterator.PatternMatchIterator getNextNodes() - Method in class cc.mallet.util.search.AStarNode getNextNodes() - Method in class cc.mallet.util.search.SearchNode Get an iterator over the new search nodes reachable from this node by state transitions. getNextStates() - Method in interface cc.mallet.util.search.SearchState Get an iterator over the states with transitions from this state. getNonNegated() - Method in class cc.mallet.pipe.tsf.OffsetFeatureConjunction getNstatesExpl() - Method in class cc.mallet.fst.SumLatticeBeam getNumBatches() - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getNumBatches() - Method in interface cc.mallet.optimize.Optimizable.ByCombiningBatchGradient getNumClasses() - Method in class cc.mallet.types.PerLabelInfoGain getNumClusters() - Method in class cc.mallet.cluster.Clustering getNumCols() - Method in class cc.mallet.types.Matrix2 Deprecated. getNumConstrainedLabels() - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints.MaxEntL2IndGEConstraint getNumConstrainedLabels() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints.OneLabelL2IndGEConstraint getNumConstrainedLabels() - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint getNumDescendants() - Method in class cc.mallet.classify.C45.Node Count the number of non-leaf descendant nodes getNumDimensions() - Method in interface cc.mallet.types.ConstantMatrix getNumDimensions() - Method in class cc.mallet.types.DenseMatrix getNumDimensions() - Method in class cc.mallet.types.DenseVector getNumDimensions() - Method in class cc.mallet.types.Matrix2 Deprecated. getNumDimensions() - Method in class cc.mallet.types.Matrixn getNumDimensions() - Method in class cc.mallet.types.SparseMatrixn getNumDimensions() - Method in class cc.mallet.types.SparseVector ACCESSORS getNumDocuments() - Method in class cc.mallet.extract.Extraction getNumericProperty(String) - Method in class cc.mallet.grmm.types.Variable getNumericProperty(String) - Method in class cc.mallet.types.Instance getNumericProperty(String) - Method in interface cc.mallet.types.PropertyHolder getNumericProperty(String) - Method in class cc.mallet.types.Token getNumericProperty(String) - Method in class cc.mallet.types.TokenSequence getNumericValue() - Method in class cc.mallet.util.PropertyList.Iterator getNumFactors() - Method in class cc.mallet.fst.CRF.Factors getNumFeaturesToDisplay() - Static method in class cc.mallet.extract.LatticeViewer getNumInstances() - Method in class cc.mallet.cluster.Clustering getNumInstances() - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable getNumInstances() - Method in interface cc.mallet.optimize.Optimizable.ByVotedPerceptron getNumIter() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer getNumLabels() - Method in class cc.mallet.fst.semi_supervised.StateLabelMap Returns the number of labels in the map. getNumOutcomes() - Method in class cc.mallet.grmm.types.Variable getNumParameters() - Method in class cc.mallet.classify.MaxEnt getNumParameters(Pipe) - Static method in class cc.mallet.classify.MaxEnt getNumParameters() - Method in class cc.mallet.classify.MaxEntOptimizableByGE getNumParameters() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution getNumParameters() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood getNumParameters() - Method in class cc.mallet.classify.PRAuxClassifierOptimizable getNumParameters() - Method in class cc.mallet.fst.CRF getNumParameters() - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getNumParameters() - Method in class cc.mallet.fst.CRFOptimizableByGradientValues getNumParameters() - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getNumParameters() - Method in class cc.mallet.fst.CRFTrainerByValueGradients.OptimizableCRF getNumParameters() - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization getNumParameters() - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByGE getNumParameters() - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getNumParameters() - Method in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL getNumParameters() - Method in class cc.mallet.fst.ThreadedOptimizable getNumParameters() - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF getNumParameters() - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable getNumParameters() - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable getNumParameters() - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable getNumParameters() - Method in interface cc.mallet.optimize.Optimizable getNumParameters() - Method in class cc.mallet.optimize.OptimizableCollection.ByGradientValue getNumParameters() - Method in class cc.mallet.topics.DMROptimizable getNumRecords() - Method in class cc.mallet.extract.Extraction getNumRows() - Method in class cc.mallet.types.Matrix2 Deprecated. getNumSplitPointsForBestFeature() - Method in class cc.mallet.types.GainRatio getNumStates() - Method in class cc.mallet.fst.semi_supervised.StateLabelMap Returns the number of states in the map. getNumTopics() - Method in class cc.mallet.topics.LDAHyper Deprecated. getNumTopics() - Method in class cc.mallet.topics.ParallelTopicModel getNumTopics() - Method in class cc.mallet.topics.PolylingualTopicModel getNumTopics() - Method in class cc.mallet.topics.SimpleLDA getNumVars() - Method in class cc.mallet.grmm.types.AbstractTableFactor getNumWeakClassifiers() - Method in class cc.mallet.classify.AdaBoost Get the number of weak classifiers in this ensemble classifier getNumWeakClassifiers() - Method in class cc.mallet.classify.AdaBoostM2 Get the number of weak classifiers in this ensemble classifier getObject(Variable) - Method in class cc.mallet.grmm.types.Assignment getObject(int, Variable) - Method in class cc.mallet.grmm.types.Assignment getObjectAtPosition(int) - Method in class cc.mallet.types.FeatureSequence getObjectAtPosition(int) - Method in class cc.mallet.types.FeatureSequenceWithBigrams getObjectAtRank(int) - Method in class cc.mallet.types.RankedFeatureVector getObjectIndices(Object[], Alphabet, boolean) - Static method in class cc.mallet.types.FeatureVector getObjectValue() - Method in class cc.mallet.util.PropertyList.Iterator getOffsets() - Method in class cc.mallet.pipe.tsf.OffsetFeatureConjunction getOldClusters() - Method in class cc.mallet.cluster.neighbor_evaluator.AgglomerativeNeighbor getOldMessages() - Method in class cc.mallet.grmm.inference.gbp.AbstractMessageStrategy getOldMessages() - Method in interface cc.mallet.grmm.inference.gbp.MessageStrategy getOptimizable(InstanceList) - Method in class cc.mallet.classify.MaxEntGERangeTrainer getOptimizable(InstanceList) - Method in class cc.mallet.classify.MaxEntGETrainer getOptimizable() - Method in class cc.mallet.classify.MaxEntTrainer getOptimizable(InstanceList) - Method in class cc.mallet.classify.MaxEntTrainer getOptimizable(InstanceList, MaxEnt) - Method in class cc.mallet.classify.MaxEntTrainer getOptimizable(InstanceList) - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByGE getOptimizable() - Method in class cc.mallet.fst.ThreadedOptimizable getOptimizable() - Method in class cc.mallet.optimize.AGIS getOptimizable() - Method in class cc.mallet.optimize.ConjugateGradient getOptimizable() - Method in class cc.mallet.optimize.GradientAscent getOptimizable() - Method in class cc.mallet.optimize.LimitedMemoryBFGS getOptimizable() - Method in interface cc.mallet.optimize.Optimizer getOptimizable() - Method in class cc.mallet.optimize.OrthantWiseLimitedMemoryBFGS getOptimizableByGradientValueObjects() - Method in class cc.mallet.fst.CRFTrainerByValueGradients getOptimizableCRF(InstanceList) - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getOptimizableCRF(InstanceList) - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getOptimizableCRF(InstanceList) - Method in class cc.mallet.fst.CRFTrainerByValueGradients Returns an optimizable CRF that contains a collection of objective functions. getOptimizableMEMM(InstanceList) - Method in class cc.mallet.fst.MEMMTrainer getOptimizer() - Method in interface cc.mallet.classify.ClassifierTrainer.ByOptimization getOptimizer() - Method in class cc.mallet.classify.MaxEntGERangeTrainer getOptimizer() - Method in class cc.mallet.classify.MaxEntGETrainer getOptimizer() - Method in class cc.mallet.classify.MaxEntL1Trainer getOptimizer(InstanceList) - Method in class cc.mallet.classify.MaxEntL1Trainer getOptimizer() - Method in class cc.mallet.classify.MaxEntPRTrainer getOptimizer() - Method in class cc.mallet.classify.MaxEntTrainer getOptimizer(InstanceList) - Method in class cc.mallet.classify.MaxEntTrainer This method is called by the train method. getOptimizer(InstanceList) - Method in class cc.mallet.fst.CRFTrainerByL1LabelLikelihood getOptimizer() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getOptimizer(InstanceList) - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getOptimizer() - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getOptimizer(InstanceList) - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getOptimizer() - Method in class cc.mallet.fst.CRFTrainerByValueGradients getOptimizer(InstanceList) - Method in class cc.mallet.fst.CRFTrainerByValueGradients Returns a L-BFGS optimizer, creating if one doesn't exist. getOptimizer() - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByEntropyRegularization getOptimizer(Optimizable.ByGradientValue) - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByGE getOptimizer() - Method in class cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR getOptimizer() - Method in interface cc.mallet.fst.TransducerTrainer.ByOptimization getOriginal() - Method in class cc.mallet.cluster.neighbor_evaluator.Neighbor getOutput() - Method in class cc.mallet.fst.CRF.TransitionIterator getOutput() - Method in class cc.mallet.fst.FeatureTransducer.TransitionIterator getOutput() - Method in class cc.mallet.fst.HMM.TransitionIterator getOutput() - Method in class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator getOutput() - Method in class cc.mallet.fst.Transducer.TransitionIterator The output symbol or object appearing on this transition. getOutputAlphabet() - Method in class cc.mallet.fst.CRF getOutputAlphabet() - Method in class cc.mallet.fst.FeatureTransducer getOutputAlphabet() - Method in class cc.mallet.fst.HMM getOutputAlphabet(int) - Method in class cc.mallet.grmm.util.LabelsAssignment getOutputPipe() - Method in class cc.mallet.fst.Transducer getOutputPositionIncrement() - Method in class cc.mallet.fst.Transducer.TransitionIterator The number of output positions that this transition produces. getParameter(int) - Method in class cc.mallet.classify.MaxEntOptimizableByGE getParameter(int) - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution getParameter(int) - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood getParameter(int) - Method in class cc.mallet.classify.PRAuxClassifierOptimizable getParameter(int) - Method in class cc.mallet.fst.CRF.Factors getParameter(int, int, int) - Method in class cc.mallet.fst.CRF Only gets the parameter from the first group of parameters. getParameter(int, int, int, int) - Method in class cc.mallet.fst.CRF getParameter(int) - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getParameter(int) - Method in class cc.mallet.fst.CRFOptimizableByGradientValues getParameter(int) - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getParameter(int) - Method in class cc.mallet.fst.CRFTrainerByValueGradients.OptimizableCRF getParameter(int) - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization getParameter(int) - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByGE getParameter(int) - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getParameter(int) - Method in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL getParameter(int) - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getParameter(int) - Method in class cc.mallet.fst.ThreadedOptimizable getParameter(int) - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF getParameter(int) - Method in interface cc.mallet.optimize.Optimizable getParameter(int) - Method in class cc.mallet.optimize.OptimizableCollection.ByGradientValue getParameter(int) - Method in class cc.mallet.topics.DMROptimizable getParameters() - Method in class cc.mallet.classify.MaxEnt getParameters(double[]) - Method in class cc.mallet.classify.MaxEntOptimizableByGE getParameters(double[]) - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution getParameters(double[]) - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood getParameters() - Method in class cc.mallet.classify.MCMaxEnt getParameters() - Method in class cc.mallet.classify.PRAuxClassifier getParameters(double[]) - Method in class cc.mallet.classify.PRAuxClassifierOptimizable getParameters(double[]) - Method in class cc.mallet.fst.CRF.Factors getParameters() - Method in class cc.mallet.fst.CRF getParameters(double[]) - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getParameters(double[]) - Method in class cc.mallet.fst.CRFOptimizableByGradientValues getParameters(double[]) - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getParameters(double[]) - Method in class cc.mallet.fst.CRFTrainerByValueGradients.OptimizableCRF getParameters(double[]) - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization getParameters(double[]) - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByGE getParameters(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getParameters(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL getParameters(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getParameters(double[]) - Method in class cc.mallet.fst.ThreadedOptimizable getParameters(double[]) - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF getParameters(double[]) - Method in class cc.mallet.grmm.learning.PiecewiseACRFTrainer.Maxable getParameters(double[]) - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer.Maxable getParameters(double[]) - Method in class cc.mallet.grmm.learning.PwplACRFTrainer.Maxable getParameters(double[]) - Method in interface cc.mallet.optimize.Optimizable getParameters(double[]) - Method in class cc.mallet.optimize.OptimizableCollection.ByGradientValue getParameters(double[]) - Method in class cc.mallet.topics.DMROptimizable getParametersAbsNorm() - Method in class cc.mallet.fst.CRF.Factors getParametersAbsNorm() - Method in class cc.mallet.fst.CRF getParent() - Method in class cc.mallet.classify.C45.Node getParent(Object) - Method in class cc.mallet.grmm.types.Tree getParent() - Method in class cc.mallet.util.search.SearchNode The node that generated this node. getParents() - Method in class cc.mallet.grmm.types.CPT getPattern() - Method in class cc.mallet.util.CharSequenceLexer getPerClassFeatureSelection() - Method in class cc.mallet.classify.Classifier getPerClassFeatureSelection() - Method in class cc.mallet.classify.MaxEnt getPerLabelFeatureSelection() - Method in class cc.mallet.types.InstanceList getPipe() - Method in class cc.mallet.cluster.Clusterer getPipe(int) - Method in class cc.mallet.pipe.SerialPipes getPipe() - Method in class cc.mallet.types.InstanceList Returns the pipe through which each added Instance is passed, which may be null. getPosition() - Method in interface cc.mallet.util.search.QueueElement Get the queue position of this element. getPosition() - Method in class cc.mallet.util.search.SearchNode getPositivePercent(Label, double) - Method in class cc.mallet.types.ROCData Gets the estimated percentage of training events that exceed the threshold. getPrecision(InstanceList, int) - Method in class cc.mallet.classify.Classifier getPrecision(InstanceList, Labeling) - Method in class cc.mallet.classify.Classifier getPrecision(InstanceList, Object) - Method in class cc.mallet.classify.Classifier getPrecision(int) - Method in class cc.mallet.classify.evaluate.ConfusionMatrix Returns the precision of this predicted class getPrecision(Object) - Method in class cc.mallet.classify.Trial Calculate the precision of the classifier on an instance list for a particular target entry getPrecision(Labeling) - Method in class cc.mallet.classify.Trial getPrecision(int) - Method in class cc.mallet.classify.Trial Calculate the precision for a particular target index from an array list of classifications getPrecision(Label, double) - Method in class cc.mallet.types.ROCData Gets the precision for a specified label and threshold. getPrecisionForScore(Label, double) - Method in class cc.mallet.types.ROCData Gets the precision for a specified label and score. getPredicted(int) - Method in class cc.mallet.fst.Segment getPredicted() - Method in class cc.mallet.fst.Segment getPredictedLabels() - Method in class cc.mallet.extract.DocumentExtraction getPreferredSize() - Method in class cc.mallet.classify.evaluate.Graph getPriority() - Method in interface cc.mallet.util.search.QueueElement Get this element's priority. getPriority() - Method in class cc.mallet.util.search.SearchNode getPriorMultinomialEstimator() - Method in class cc.mallet.classify.NaiveBayesEMTrainer getPriorMultinomialEstimator() - Method in class cc.mallet.classify.NaiveBayesTrainer Get the MultinomialEstimator instance used to specify the type of estimator for priors. getPriors() - Method in class cc.mallet.classify.NaiveBayes getProbEstimator() - Method in class cc.mallet.topics.ParallelTopicModel Return a tool for evaluating the marginal probability of new documents under this model getProjectionValueContrib(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint getProperties() - Method in class cc.mallet.types.Instance Deprecated. getProperties() - Method in interface cc.mallet.types.PropertyHolder getProperties() - Method in class cc.mallet.types.Token getProperties() - Method in class cc.mallet.types.TokenSequence getProperty(String) - Method in class cc.mallet.types.Instance getProperty(String) - Method in interface cc.mallet.types.PropertyHolder getProperty(String) - Method in class cc.mallet.types.Token getProperty(String) - Method in class cc.mallet.types.TokenSequence getProvidedOutput() - Method in class cc.mallet.fst.MaxLatticeDefault getPrunedAlphabet(int) - Method in class cc.mallet.pipe.FeatureCountPipe Returns a new alphabet that contains only features at or above the specified limit. getQValue() - Method in class cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR getRandom() - Static method in class cc.mallet.grmm.learning.DefaultAcrfTrainer getRank(Label) - Method in class cc.mallet.types.Label getRank(int) - Method in class cc.mallet.types.Label getRank(Label) - Method in interface cc.mallet.types.Labeling getRank(int) - Method in interface cc.mallet.types.Labeling getRank(Label) - Method in class cc.mallet.types.LabelVector getRank(int) - Method in class cc.mallet.types.LabelVector getRank(Object) - Method in class cc.mallet.types.RankedFeatureVector getRank(int) - Method in class cc.mallet.types.RankedFeatureVector getRank1Percent() - Method in class cc.mallet.topics.TopicModelDiagnostics getRecall(InstanceList, int) - Method in class cc.mallet.classify.Classifier getRecall(InstanceList, Labeling) - Method in class cc.mallet.classify.Classifier getRecall(InstanceList, Object) - Method in class cc.mallet.classify.Classifier getRecall(Object) - Method in class cc.mallet.classify.Trial Calculate the recall of the classifier on an instance list for a particular target entry getRecall(Labeling) - Method in class cc.mallet.classify.Trial getRecall(int) - Method in class cc.mallet.classify.Trial Calculate the recall for a particular target index from an array list of classifications getRecall(Label, double) - Method in class cc.mallet.types.ROCData Gets the recall rate for a specified label and threshold. getRecord(int) - Method in class cc.mallet.extract.Extraction getRegularization() - Method in class cc.mallet.classify.MaxEntOptimizableByGE getRightChild() - Method in class cc.mallet.classify.C45.Node getRoot() - Method in class cc.mallet.classify.C45 getRoot() - Method in class cc.mallet.classify.DecisionTree getRoot() - Method in class cc.mallet.grmm.types.Tree getRootLogger() - Method in class cc.mallet.util.MalletLogger Convenience method for finding the root logger. getRow(int) - Method in class cc.mallet.grmm.types.Assignment getSampledDistribution(Instance, int, int, int) - Method in class cc.mallet.topics.TopicInferencer Use Gibbs sampling to infer a topic distribution. getScalingFactor() - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization getScatterMatrix(double[][]) - Static method in class cc.mallet.util.MVNormal getScore(FeatureVector, int, double[]) - Method in class cc.mallet.classify.constraints.pr.MaxEntL2FLPRConstraints getScore(FeatureVector, int, double[]) - Method in interface cc.mallet.classify.constraints.pr.MaxEntPRConstraint getScore(Clustering, int, int) - Method in class cc.mallet.cluster.GreedyAgglomerative getScore(FeatureVector, int, int, int, double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints getScore(int, double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2IndPRConstraints.OneLabelL2IndPRConstraint getScore(FeatureVector, int, int, int, double[]) - Method in class cc.mallet.fst.semi_supervised.pr.constraints.OneLabelL2PRConstraints getScore(FeatureVector, int, int, int, double[]) - Method in interface cc.mallet.fst.semi_supervised.pr.constraints.PRConstraint getSecondString() - Method in class cc.mallet.types.StringEditVector getSecondStringChar(int) - Method in class cc.mallet.types.StringEditVector getSegmentConfidences() - Method in class cc.mallet.fst.confidence.ConstrainedViterbiTransducerCorrector getSegmentConfidences() - Method in class cc.mallet.fst.confidence.TransducerConfidenceEstimator getSegmentInputSequence() - Method in class cc.mallet.fst.Segment getSepset(VarSet, VarSet) - Method in class cc.mallet.grmm.inference.JunctionTree getSepsetPot(VarSet, VarSet) - Method in class cc.mallet.grmm.inference.JunctionTree getSize() - Method in class cc.mallet.classify.C45 getSize() - Method in class cc.mallet.classify.C45.Node getSortedTopicWords(int) - Method in class cc.mallet.topics.LDAHyper Deprecated. getSortedWords() - Method in class cc.mallet.topics.ParallelTopicModel Return an array of sorted sets (one set per topic). getSource() - Method in class cc.mallet.types.Instance getSourceState() - Method in class cc.mallet.fst.CRF.TransitionIterator getSourceState() - Method in class cc.mallet.fst.FeatureTransducer.TransitionIterator getSourceState() - Method in class cc.mallet.fst.HMM.TransitionIterator getSourceState() - Method in class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator getSourceState() - Method in class cc.mallet.fst.Transducer.TransitionIterator The state we were in before taking this transition. getSpan() - Method in class cc.mallet.extract.LabeledSpan getSpan(int) - Method in class cc.mallet.extract.LabeledSpans getSpan(int) - Method in class cc.mallet.extract.StringTokenization getSpan(int) - Method in interface cc.mallet.extract.Tokenization getSplitFeature() - Method in class cc.mallet.classify.C45.Node getSplitFeature() - Method in class cc.mallet.classify.DecisionTree.Node getSplitInfoGain() - Method in class cc.mallet.classify.DecisionTree.Node getStart() - Method in class cc.mallet.fst.Segment getStartIdx() - Method in class cc.mallet.extract.LabeledSpan getStartIdx() - Method in interface cc.mallet.extract.Span Returns an integer index identifying the start of this span. getStartIdx() - Method in class cc.mallet.extract.StringSpan getStartOffset() - Method in class cc.mallet.util.CharSequenceLexer getStartOffset() - Method in interface cc.mallet.util.Lexer getStartTag() - Method in class cc.mallet.fst.Segment getState(String) - Method in class cc.mallet.fst.CRF getState(int) - Method in class cc.mallet.fst.CRF getState(int) - Method in class cc.mallet.fst.FeatureTransducer getState(String) - Method in class cc.mallet.fst.HMM getState(int) - Method in class cc.mallet.fst.HMM getState(int) - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getState(int) - Method in class cc.mallet.fst.Transducer getState() - Method in class cc.mallet.util.search.SearchNode The state for this search node. getStateAlphabet() - Method in class cc.mallet.fst.semi_supervised.StateLabelMap Returns the state alphabet. getStateIndices(int) - Method in class cc.mallet.fst.semi_supervised.StateLabelMap Returns the state indices that map to the label index. getStateIter() - Method in class cc.mallet.util.search.SearchNode.NextNodeIterator getStepSize() - Method in class cc.mallet.optimize.ConjugateGradient getStpmax() - Method in class cc.mallet.optimize.GradientAscent getString1() - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString1BlockAtIndex(int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString1Char(int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString1EOBIndex(String) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString1EOBIndex(String, int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString1IndexOf(String, int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString1Length() - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString2() - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString2BlockAtIndex(int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString2Char(int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString2EOBIndex(String) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString2EOBIndex(String, int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString2IndexOf(String, int) - Method in class cc.mallet.types.StringEditFeatureVectorSequence getString2Length() - Method in class cc.mallet.types.StringEditFeatureVectorSequence getStringBufferName() - Method in class cc.mallet.classify.C45.Node getStructureType() - Method in class cc.mallet.grmm.learning.PseudolikelihoodACRFTrainer getSubDirs(File) - Static method in class cc.mallet.cluster.tui.Text2Clusterings getSumLatticeFactory() - Method in class cc.mallet.fst.Transducer getSwapIns() - Method in class cc.mallet.types.PagedInstanceList getSwapInTime() - Method in class cc.mallet.types.PagedInstanceList getSwapOuts() - Method in class cc.mallet.types.PagedInstanceList getSwapOutTime() - Method in class cc.mallet.types.PagedInstanceList getTarget() - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints.MaxEntFLGEConstraint getTarget() - Method in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints.MaxEntFLPRConstraint getTarget() - Method in class cc.mallet.extract.DocumentExtraction getTarget() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints.OneLabelGEConstraint getTarget() - Method in class cc.mallet.types.Instance getTargetAlphabet() - Method in class cc.mallet.extract.CRFExtractor getTargetAlphabet() - Method in interface cc.mallet.extract.Extractor Returns an alphabet of the labels used by the extractor. getTargetAlphabet() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor getTargetAlphabet() - Method in class cc.mallet.pipe.Pipe getTargetAlphabet() - Method in class cc.mallet.types.Instance getTargetAlphabet() - Method in class cc.mallet.types.InstanceList Returns the Alphabet mapping target output labels to integers. getTargetClass() - Method in class cc.mallet.types.InstanceList Returns the Java Class 'target' field of Instances in this list. getTargetRecord(int) - Method in class cc.mallet.extract.Extraction getTargetSpans() - Method in class cc.mallet.extract.DocumentExtraction getTctIter() - Method in class cc.mallet.fst.SumLatticeBeam getTemplate() - Method in class cc.mallet.grmm.learning.ACRF.UnrolledVarSet getTemplates() - Method in class cc.mallet.grmm.learning.ACRF getTest() - Method in class cc.mallet.topics.LDAStream getTestingData() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer getText() - Method in class cc.mallet.extract.LabeledSpan getText() - Method in interface cc.mallet.extract.Span Returns a textual representatio of the span, suitable for XML output, e.g. getText() - Method in class cc.mallet.types.Token getThresholdAtRank(int) - Method in class cc.mallet.types.GainRatio getThresholds() - Method in class cc.mallet.types.ROCData Gets the thresholds being tracked getTokenDocumentDiscrepancies() - Method in class cc.mallet.topics.TopicModelDiagnostics getTokenizationFilter() - Method in class cc.mallet.extract.CRFExtractor getTokenizationPipe() - Method in class cc.mallet.extract.CRFExtractor getTokenizationPipe() - Method in interface cc.mallet.extract.Extractor Returns the pipe used by this extractor to tokenize the input. getTokenizationPipe() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractor getTokensPerTopic() - Method in class cc.mallet.topics.LDA Deprecated. getTokensPerTopic() - Method in class cc.mallet.topics.MarginalProbEstimator getTokensPerTopic(int[]) - Method in class cc.mallet.topics.TopicModelDiagnostics getTokensPerTopic() - Method in class cc.mallet.topics.WorkerRunnable getTokenString() - Method in class cc.mallet.util.CharSequenceLexer getTokenString() - Method in interface cc.mallet.util.Lexer getTopicAlphabet() - Method in class cc.mallet.topics.LDAHyper Deprecated. getTopicAlphabet() - Method in class cc.mallet.topics.ParallelTopicModel getTopicAlphabet() - Method in class cc.mallet.topics.PolylingualTopicModel getTopicAlphabet() - Method in class cc.mallet.topics.SimpleLDA getTopicDocCounts() - Method in class cc.mallet.topics.WorkerRunnable getTopicProbabilities(int) - Method in class cc.mallet.topics.ParallelTopicModel Get the smoothed distribution over topics for a training instance. getTopicProbabilities(LabelSequence) - Method in class cc.mallet.topics.ParallelTopicModel Get the smoothed distribution over topics for a topic sequence, which may be from the training set or from a new instance with topics assigned by an inferencer. getTopicTotals() - Method in class cc.mallet.topics.SimpleLDA getTopWords(int) - Method in class cc.mallet.topics.ParallelTopicModel Return an array (one element for each topic) of arrays of words, which are the most probable words for that topic in descending order. getTotalMessagesSent() - Static method in class cc.mallet.grmm.inference.AbstractBeliefPropagation Returns the total number of messages all BP inferencers have sent in the current Java image. getTotalMessagesSent() - Method in class cc.mallet.grmm.inference.JunctionTreeInferencer Returns the total number of messages this inferencer has sent. getTotalNodes() - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF getTotalValue() - Method in class cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR getTotalWeight() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getTotalWeight() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getTotalWeight() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getTotalWeight() - Method in interface cc.mallet.fst.SumLattice getTotalWeight() - Method in class cc.mallet.fst.SumLatticeBeam getTotalWeight() - Method in class cc.mallet.fst.SumLatticeDefault getTotalWeight() - Method in class cc.mallet.fst.SumLatticeScaling getTrainer() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer getTrainingData() - Method in class cc.mallet.grmm.learning.extract.ACRFExtractorTrainer getTransducer() - Method in class cc.mallet.fst.confidence.TransducerConfidenceEstimator getTransducer() - Method in class cc.mallet.fst.CRF.State getTransducer() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getTransducer() - Method in class cc.mallet.fst.CRFTrainerByStochasticGradient getTransducer() - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getTransducer() - Method in class cc.mallet.fst.CRFTrainerByValueGradients getTransducer() - Method in class cc.mallet.fst.FeatureTransducer.State getTransducer() - Method in class cc.mallet.fst.HMM.State getTransducer() - Method in class cc.mallet.fst.HMMTrainerByLikelihood getTransducer() - Method in interface cc.mallet.fst.MaxLattice getTransducer() - Method in class cc.mallet.fst.MaxLatticeDefault getTransducer() - Method in class cc.mallet.fst.MEMMTrainer getTransducer() - Method in class cc.mallet.fst.NoopTransducerTrainer getTransducer() - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByEntropyRegularization getTransducer() - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByGE getTransducer() - Method in class cc.mallet.fst.semi_supervised.CRFTrainerByLikelihoodAndGE getTransducer() - Method in class cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR getTransducer() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getTransducer() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getTransducer() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getTransducer() - Method in class cc.mallet.fst.ShallowTransducerTrainer Deprecated. getTransducer() - Method in interface cc.mallet.fst.SumLattice getTransducer() - Method in class cc.mallet.fst.SumLatticeBeam getTransducer() - Method in class cc.mallet.fst.SumLatticeDefault getTransducer() - Method in class cc.mallet.fst.SumLatticeScaling getTransducer() - Method in class cc.mallet.fst.Transducer.State getTransducer() - Method in class cc.mallet.fst.Transducer.TransitionIterator getTransducer() - Method in class cc.mallet.fst.TransducerTrainer getTransitionEstimator() - Method in class cc.mallet.fst.FeatureTransducer.State getTrimmedClassifier(int) - Method in class cc.mallet.classify.AdaBoost Return an AdaBoost classifier that uses only the first numWeakClassifiersToUse weak learners. getTrimmedClassifier(int) - Method in class cc.mallet.classify.AdaBoostM2 Return an AdaBoostM2 classifier that uses only the first numWeakClassifiersToUse weak learners. getTruth(int) - Method in class cc.mallet.fst.Segment getTruth() - Method in class cc.mallet.fst.Segment getTypeTopicCounts() - Method in class cc.mallet.topics.LDA Deprecated. getTypeTopicCounts() - Method in class cc.mallet.topics.MarginalProbEstimator getTypeTopicCounts() - Method in class cc.mallet.topics.SimpleLDA getTypeTopicCounts() - Method in class cc.mallet.topics.WorkerRunnable getUniverse() - Method in class cc.mallet.grmm.types.Variable getUnlabeledDataWeight() - Method in class cc.mallet.classify.NaiveBayesEMTrainer getUnnormalizedClassificationScores(Instance, double[]) - Method in class cc.mallet.classify.MaxEnt getUnnormalizedClassificationScores(Instance, double[]) - Method in class cc.mallet.classify.MCMaxEnt getUnnormalizedClassificationScores(Instance, double[]) - Method in class cc.mallet.classify.RankMaxEnt returns unnormalized scores, corresponding to the score an element of the InstanceList being the "top" instance getUnrolledVarSet(int) - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph getUnrolledVarSet(Factor) - Method in class cc.mallet.grmm.learning.ACRF.UnrolledGraph getUseForwardBackwardBeam() - Method in class cc.mallet.fst.SumLatticeBeam getUseHyperbolicPriorSharpness() - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getUseHyperbolicPriorSharpness() - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getUseHyperbolicPriorSharpness() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getUseHyperbolicPriorSlope() - Method in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood getUseHyperbolicPriorSlope() - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getUseHyperbolicPriorSlope() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getUseInertia() - Method in class cc.mallet.grmm.inference.gbp.ParentChildGBP getUseSparseWeights() - Method in class cc.mallet.fst.CRFTrainerByLabelLikelihood getUseSparseWeights() - Method in class cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood getValidationInstances() - Method in class cc.mallet.classify.ClassifierTrainer getValue(int) - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints.MaxEntFLGEConstraint getValue() - Method in interface cc.mallet.classify.constraints.ge.MaxEntGEConstraint Returns the total constraint value. getValue() - Method in class cc.mallet.classify.constraints.ge.MaxEntKLFLGEConstraints getValue(int) - Method in class cc.mallet.classify.constraints.ge.MaxEntKLFLGEConstraints.MaxEntKLFLGEConstraint getValue() - Method in class cc.mallet.classify.constraints.ge.MaxEntL2FLGEConstraints getValue(int) - Method in class cc.mallet.classify.constraints.ge.MaxEntL2FLGEConstraints.MaxEntL2FLGEConstraint getValue() - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints getValue(int) - Method in class cc.mallet.classify.constraints.ge.MaxEntRangeL2FLGEConstraints.MaxEntL2IndGEConstraint getValue() - Method in class cc.mallet.classify.MaxEntOptimizableByGE getValue() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution Return the log probability of the training label distributions getValue() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood getValue() - Method in class cc.mallet.classify.PRAuxClassifierOptimizable getValue() - Method in class cc.mallet.fst.CRFOptimizableByGradientValues Returns the log probability of the training sequence labels and the prior over parameters. getValue() - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood Returns the log probability of the training sequence labels and the prior over parameters. getValue() - Method in class cc.mallet.fst.CRFTrainerByValueGradients.OptimizableCRF Returns the log probability of the training sequence labels and the prior over parameters. getValue() - Method in interface cc.mallet.fst.semi_supervised.constraints.GEConstraint Returns the total constraint value. getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints getValue(int) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints.OneLabelGEConstraint getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelKLGEConstraints getValue(int) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelKLGEConstraints.OneLabelGEKLConstraint getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2GEConstraints getValue(int) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2GEConstraints.OneLabelGEL2Constraint getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.SelfTransitionGEConstraint getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints getValue(int, int) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelGEConstraints.TwoLabelGEConstraint getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelKLGEConstraints getValue(int, int) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelKLGEConstraints.TwoLabelKLGEConstraint getValue() - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelL2GEConstraints getValue(int, int) - Method in class cc.mallet.fst.semi_supervised.constraints.TwoLabelL2GEConstraints.TwoLabelL2GEConstraint getValue() - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization getValue() - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByGE getValue() - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR Returns the log probability of the training sequence labels and the prior over parameters. getValue() - Method in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL getValue() - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getValue() - Method in class cc.mallet.fst.ThreadedOptimizable getValue() - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF Returns the log probability of the training sequence labels getValue() - Method in class cc.mallet.grmm.util.CachingOptimizable.ByGradient getValue() - Method in interface cc.mallet.optimize.Optimizable.ByGISUpdate getValue() - Method in interface cc.mallet.optimize.Optimizable.ByGradientValue getValue() - Method in interface cc.mallet.optimize.Optimizable.ByValue getValue() - Method in class cc.mallet.optimize.OptimizableCollection.ByGradientValue getValue() - Method in class cc.mallet.topics.DMROptimizable The log probability of the observed count vectors given the features. getValueAndGradient(double[]) - Method in class cc.mallet.classify.PRAuxClassifierOptimizable getValueAtRank(int) - Method in class cc.mallet.types.Label getValueAtRank(int) - Method in interface cc.mallet.types.Labeling getValueAtRank(int) - Method in class cc.mallet.types.LabelVector getValueAtRank(int) - Method in class cc.mallet.types.RankedFeatureVector getValueCalls() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution Counts how many times this trainer has computed the log probability of training labels. getValueCalls() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood Counts how many times this trainer has computed the log probability of training labels. getValueCalls() - Method in class cc.mallet.classify.MCMaxEntTrainer Counts how many times this trainer has computed the log probability of training labels. getValueContribution(int) - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelL2RangeGEConstraints.OneLabelL2IndGEConstraint getValueGradient(double[]) - Method in class cc.mallet.classify.MaxEntOptimizableByGE getValueGradient(double[]) - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution getValueGradient(double[]) - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood getValueGradient(double[]) - Method in class cc.mallet.classify.PRAuxClassifierOptimizable getValueGradient(double[]) - Method in class cc.mallet.fst.CRFOptimizableByGradientValues getValueGradient(double[]) - Method in class cc.mallet.fst.CRFOptimizableByLabelLikelihood getValueGradient(double[]) - Method in class cc.mallet.fst.CRFTrainerByValueGradients.OptimizableCRF getValueGradient(double[]) - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByEntropyRegularization getValueGradient(double[]) - Method in class cc.mallet.fst.semi_supervised.CRFOptimizableByGE getValueGradient(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.ConstraintsOptimizableByPR getValueGradient(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.CRFOptimizableByKL getValueGradient(double[]) - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getValueGradient(double[]) - Method in class cc.mallet.fst.ThreadedOptimizable Returns the gradient, re-computes if gradient is stale. getValueGradient(double[]) - Method in class cc.mallet.grmm.learning.ACRF.MaximizableACRF Computes the graident of the penalized log likelihood of the ACRF, and returns it in buf[]. getValueGradient(double[]) - Method in class cc.mallet.grmm.util.CachingOptimizable.ByGradient getValueGradient(double[]) - Method in interface cc.mallet.optimize.Optimizable.ByGradient getValueGradient(double[]) - Method in interface cc.mallet.optimize.Optimizable.ByGradientValue getValueGradient(double[]) - Method in class cc.mallet.optimize.OptimizableCollection.ByGradientValue getValueGradient(double[]) - Method in class cc.mallet.topics.DMROptimizable getValueGradientCalls() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelDistribution Counts how many times this trainer has computed the gradient of the log probability of training labels. getValueGradientCalls() - Method in class cc.mallet.classify.MaxEntOptimizableByLabelLikelihood Counts how many times this trainer has computed the gradient of the log probability of training labels. getValueGradientCalls() - Method in class cc.mallet.classify.MCMaxEntTrainer Counts how many times this trainer has computed the gradient of the log probability of training labels. getValueGradientForInstance(int, double[]) - Method in interface cc.mallet.optimize.Optimizable.ByVotedPerceptron getValueHessian(double[][]) - Method in interface cc.mallet.optimize.Optimizable.ByHessian getValueMatrix() - Method in class cc.mallet.grmm.types.AbstractTableFactor getValueMatrix() - Method in class cc.mallet.grmm.types.LogTableFactor getValueMatrix() - Method in class cc.mallet.grmm.types.TableFactor getValues() - Method in class cc.mallet.grmm.types.AbstractTableFactor getValues() - Method in class cc.mallet.types.SparseVector getVariable(int) - Method in class cc.mallet.grmm.types.AbstractFactor getVariable(int) - Method in class cc.mallet.grmm.types.AbstractTableFactor getVariable(int) - Method in class cc.mallet.grmm.types.Assignment getVariable(int) - Method in class cc.mallet.grmm.types.CPT getVariable(int) - Method in interface cc.mallet.grmm.types.Factor getVariable(int) - Method in class cc.mallet.grmm.types.FactorGraph getVars() - Method in class cc.mallet.grmm.types.Assignment Returns all variables which are assigned to. getVerticesIterator() - Method in class cc.mallet.grmm.types.Tree getViterbiInferencer() - Method in class cc.mallet.grmm.learning.ACRF getViterbiNode(int, int) - Method in class cc.mallet.fst.MaxLatticeDefault getWeight() - Method in class cc.mallet.classify.constraints.ge.MaxEntFLGEConstraints.MaxEntFLGEConstraint getWeight() - Method in class cc.mallet.classify.constraints.pr.MaxEntFLPRConstraints.MaxEntFLPRConstraint getWeight() - Method in class cc.mallet.fst.CRF.TransitionIterator getWeight() - Method in class cc.mallet.fst.FeatureTransducer.TransitionIterator getWeight() - Method in class cc.mallet.fst.HMM.TransitionIterator getWeight() - Method in class cc.mallet.fst.semi_supervised.constraints.OneLabelGEConstraints.OneLabelGEConstraint getWeight() - Method in class cc.mallet.fst.semi_supervised.pr.CachedDotTransitionIterator getWeight(int, int, Sequence, Transducer.TransitionIterator) - Method in class cc.mallet.fst.semi_supervised.pr.PRAuxiliaryModel getWeight() - Method in class cc.mallet.fst.Transducer.TransitionIterator The weight (between infinity and -infinity) associated with taking this transition with this input/output. getWeight() - Method in class cc.mallet.pipe.iterator.PipeInputIterator Deprecated. getWeight() - Method in class cc.mallet.types.IDSorter getWeight() - Method in class cc.mallet.types.SequencePairAlignment getWeightNames(int) - Method in class cc.mallet.fst.CRF.State getWeights() - Method in class cc.mallet.classify.BalancedWinnow getWeights(String) - Method in class cc.mallet.fst.CRF getWeights(int) - Method in class cc.mallet.fst.CRF getWeights() - Method in class cc.mallet.fst.CRF getWeights() - Method in class cc.mallet.grmm.learning.ACRF.FixedFactorTemplate getWeights() - Method in class cc.mallet.grmm.learning.ACRF.Template Returns the weights for this clique template. getWeightsIndex(String) - Method in class cc.mallet.fst.CRF getWeightsName(int) - Method in class cc.mallet.fst.CRF getWeightsStructureChangeStamp() - Method in class cc.mallet.fst.CRF getWeightsValueChangeStamp() - Method in class cc.mallet.fst.CRF getWidth() - Method in class cc.mallet.grmm.types.UndirectedGrid getWordLengthScores() - Method in class cc.mallet.topics.TopicModelDiagnostics Low-quality topics often have lots of unusually short words. getWordLengthStandardDeviation() - Method in class cc.mallet.topics.TopicModelDiagnostics Low-quality topics often have lots of unusually short words. getWorstAveragePrecision() - Method in class cc.mallet.fst.confidence.ConfidenceEvaluator For comparison, rank segments as badly as possible (all "incorrect" before "correct"). getWrongWrongThreshold() - Method in class cc.mallet.grmm.learning.PwplACRFTrainer getXiProbability(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getXiProbability(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getXiProbability(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getXiProbability(int, Transducer.State, Transducer.State) - Method in interface cc.mallet.fst.SumLattice getXiProbability(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.SumLatticeBeam getXiProbability(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.SumLatticeDefault getXiProbability(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.SumLatticeScaling getXis() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getXis() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getXis() - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getXis() - Method in interface cc.mallet.fst.SumLattice getXis() - Method in class cc.mallet.fst.SumLatticeBeam getXis() - Method in class cc.mallet.fst.SumLatticeDefault getXis() - Method in class cc.mallet.fst.SumLatticeScaling getXiWeight(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeDefaultCachedDot getXiWeight(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticeKL getXiWeight(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.semi_supervised.pr.SumLatticePR getXiWeight(int, Transducer.State, Transducer.State) - Method in interface cc.mallet.fst.SumLattice getXiWeight(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.SumLatticeBeam getXiWeight(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.SumLatticeDefault getXiWeight(int, Transducer.State, Transducer.State) - Method in class cc.mallet.fst.SumLatticeScaling GibbsSampler - Class in cc.mallet.grmm.inference Created: Mar 28, 2005 GibbsSampler() - Constructor for class cc.mallet.grmm.inference.GibbsSampler GibbsSampler(int) - Constructor for class cc.mallet.grmm.inference.GibbsSampler GibbsSampler(Randoms, int) - Constructor for class cc.mallet.grmm.inference.GibbsSampler globalFeatureSelection - Variable in class cc.mallet.fst.CRF go() - Method in class cc.mallet.util.resources.wn.Examples GRADIENT_GAIN - Static variable in class cc.mallet.classify.MCMaxEntTrainer GradientAscent - Class in cc.mallet.optimize GradientAscent(Optimizable.ByGradientValue) - Constructor for class cc.mallet.optimize.GradientAscent GradientBracketLineOptimizer - Class in cc.mallet.optimize GradientBracketLineOptimizer(Optimizable.ByGradientValue) - Constructor for class cc.mallet.optimize.GradientBracketLineOptimizer GradientGain - Class in cc.mallet.types GradientGain(InstanceList, LabelVector[]) - Constructor for class cc.mallet.types.GradientGain GradientGain(InstanceList, Classification[]) - Constructor for class cc.mallet.types.GradientGain GradientGain.Factory - Class in cc.mallet.types GradientGain.Factory(LabelVector[]) - Constructor for class cc.mallet.types.GradientGain.Factory Graph - Class in cc.mallet.classify.evaluate Framework for standard graph. Graph(String, int, int, String, String) - Constructor for class cc.mallet.classify.evaluate.Graph Creates a Graph object Graph.Legend - Class in cc.mallet.classify.evaluate Graph.Legend() - Constructor for class cc.mallet.classify.evaluate.Graph.Legend Graph2 - Class in cc.mallet.classify.evaluate Methods for a 2-D graph Graph2(String, int, int, String, String) - Constructor for class cc.mallet.classify.evaluate.Graph2 GraphItem - Class in cc.mallet.classify.evaluate Holds data for a point on a graph GraphItem(String, int, Color) - Constructor for class cc.mallet.classify.evaluate.GraphItem Graphs - Class in cc.mallet.grmm.util Created: Dec 21, 2005 Graphs() - Constructor for class cc.mallet.grmm.util.Graphs GreedyAgglomerative - Class in cc.mallet.cluster Greedily merges Instances until convergence. GreedyAgglomerative(Pipe, NeighborEvaluator, double) - Constructor for class cc.mallet.cluster.GreedyAgglomerative GreedyAgglomerativeByDensity - Class in cc.mallet.cluster Greedily merges Instances until convergence. GreedyAgglomerativeByDensity(Pipe, NeighborEvaluator, double, boolean, Random) - Constructor for class cc.mallet.cluster.GreedyAgglomerativeByDensity growIfNecessary() - Method in class cc.mallet.types.FeatureSequence growthStopped() - Method in class cc.mallet.grmm.types.BidirectionalIntObjectMap growthStopped() - Method in class cc.mallet.types.Alphabet H HALF_LOG_TWO_PI - Static variable in class cc.mallet.types.Dirichlet hasConverged() - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation hasConverged(double) - Method in class cc.mallet.grmm.inference.AbstractBeliefPropagation hasFeature(String) - Method in class cc.mallet.fst.confidence.SequenceConfidenceInstance hashCode() - Method in class cc.mallet.grmm.types.BinaryUnaryFactor hashCode() - Method in class cc.mallet.grmm.types.BitVarSet hashCode() - Method in class cc.mallet.grmm.types.BoltzmannPairFactor hashCode() - Method in class cc.mallet.grmm.types.BoltzmannUnaryFactor hashCode() - Method in class cc.mallet.grmm.types.HashVarSet hashCode() - Method in class cc.mallet.grmm.types.ListVarSet hashCode() - Method in class cc.mallet.grmm.types.PottsTableFactor hashCode() - Method in class cc.mallet.grmm.types.UnmodifiableVarSet hashCode() - Method in class cc.mallet.types.MultiInstanceList HashedSparseVector - Class in cc.mallet.types HashedSparseVector(int[], double[], int, int, boolean, boolean, boolean) - Constructor for class cc.mallet.types.HashedSparseVector HashedSparseVector() - Constructor for class cc.mallet.types.HashedSparseVector Create an empty vector HashedSparseVector(int[], double[]) - Constructor for class cc.mallet.types.HashedSparseVector Create non-binary vector, possibly dense if "featureIndices" or possibly sparse, if not HashedSparseVector(int[]) - Constructor for class cc.mallet.types.HashedSparseVector Create binary vector HashVarSet - Class in cc.mallet.grmm.types A clique is a collection of nodes in a graph that are all adjacent. HashVarSet() - Constructor for class cc.mallet.grmm.types.HashVarSet Create an empty clique. HashVarSet(Collection) - Constructor for class cc.mallet.grmm.types.HashVarSet Create a Clique given a Collection of nodes. HashVarSet(Variable[]) - Constructor for class cc.mallet.grmm.types.HashVarSet hasInfinite - Variable in class cc.mallet.types.DenseMatrix hasInfinite - Variable in class cc.mallet.types.SparseVector hasLabel() - Method in class cc.mallet.grmm.types.BitVarSet hasNext() - Method in class cc.mallet.cluster.iterator.AllPairsIterator hasNext() - Method in class cc.mallet.cluster.iterator.PairSampleIterator hasNext() - Method in class cc.mallet.fst.CRF.Transit