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(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(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(Object) - 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
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
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) - Method in class cc.mallet.topics.ParallelTopicModel
addInstances(InstanceList[]) - Method in class cc.mallet.topics.PolylingualTopicModel
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.
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
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.
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
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.
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.topics.LDAHyper: Deprecated.
alpha - Variable in class cc.mallet.topics.MarginalProbEstimator
alpha - Variable in class cc.mallet.topics.ParallelTopicModel
alpha - Variable in class cc.mallet.topics.PolylingualTopicModel
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.ParallelTopicModel
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.
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.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.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
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
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.topics.LDAHyper: Deprecated.
beta - Variable in class cc.mallet.topics.MarginalProbEstimator
beta - Variable in class cc.mallet.topics.ParallelTopicModel
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.ParallelTopicModel
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, Variable) - 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, Variable) - 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

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
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
cachedGradient - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
cachedGradient - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood
cachedGradientChangeStamp - Variable in class cc.mallet.fst.CRFCacheStaleIndicator
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
cachedValue - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
cachedValue - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood
cachedValueChangeStamp - Variable in class cc.mallet.fst.CRFCacheStaleIndicator
cacheIndicator - Variable in class cc.mallet.fst.ThreadedOptimizable
CacheStaleIndicator - Interface in cc.mallet.fst: Indicates when the value/gradient during training becomes stale.
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.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.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.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
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
Classifier2Info - Class in cc.mallet.classify.tui: Diagnostic facilities for a vector file.
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.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
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
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
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
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
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
constraints - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood
constraints - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood
constraints - Variable in class cc.mallet.fst.CRFTrainerByStochasticGradient
constraintsFile - Static variable in class cc.mallet.classify.tui.Vectors2FeatureConstraints
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
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(int[], int) - Static method in class cc.mallet.util.ArrayUtils: Returns the number of times a value occurs in a given array.
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
createMaximizable(ACRF, InstanceList) - Method in class cc.mallet.grmm.learning.DefaultAcrfTrainer
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
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.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
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
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
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
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
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 - 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.ParallelTopicModel data - Variable in class cc.mallet.topics.PolylingualTopicModel 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.ParallelTopicModel DEFAULT_BETA - Static variable in class cc.mallet.topics.PolylingualTopicModel 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_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 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. 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 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 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() 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.BoltzmannPairFactor dumpToString() - Method in class cc.mallet.grmm.types.BoltzmannUnaryFactor 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() - 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. 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, 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 exp() - Static method in class cc.mallet.grmm.util.Flops exp(int) - Static method in class cc.mallet.grmm.util.Flops EXP_GAIN - Static variable in class cc.mallet.classify.MaxEntTrainer EXP_GAIN - Static variable in class cc.mallet.classify.MCMaxEntTrainer expectations - Variable in class cc.mallet.fst.CRFOptimizableByBatchLabelLikelihood expectations - Variable in class cc.mallet.fst.CRFOptimizableByLabelLikelihood expectations - Variable in class cc.mallet.fst.CRFTrainerByStochasticGradient 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 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.BoltzmannPairFactor extractMaxInternal(VarSet) - Method in class cc.mallet.grmm.types.BoltzmannUnaryFactor 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. FAL