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Uses of Class
cc.mallet.types.Instance

Packages that use Instance
cc.mallet.classify Classes for training and classifying instances. 
cc.mallet.cluster.iterator   
cc.mallet.cluster.tui   
cc.mallet.cluster.util   
cc.mallet.extract Unimplemented. 
cc.mallet.extract.pipe   
cc.mallet.fst Transducers, including Conditional Random Fields (CRFs). 
cc.mallet.fst.confidence   
cc.mallet.fst.tests Tests for Transducers, including Conditional Random Fields (CRFs). 
cc.mallet.grmm.learning   
cc.mallet.grmm.learning.extract   
cc.mallet.grmm.util   
cc.mallet.pipe Classes for processing arbitrary data into instances. 
cc.mallet.pipe.iterator Classes that generate instances from different kinds of input or data structures. 
cc.mallet.pipe.tests JUnit tests for pipes. 
cc.mallet.pipe.tsf TokenSequenceFeature Pipes. 
cc.mallet.share.casutton.ner   
cc.mallet.share.mccallum.ner Named entity recognizer. 
cc.mallet.share.upenn Utilities that currently include a command line wrapper for the maxent classifier. 
cc.mallet.share.upenn.ner   
cc.mallet.share.weili.ner.enron   
cc.mallet.topics   
cc.mallet.types Fundamental MALLET types, including FeatureVector, Instance, Label etc. 
 

Uses of Instance in cc.mallet.classify
 

Methods in cc.mallet.classify that return Instance
 Instance Classification.getInstance()
           
 Instance Classification.toInstance()
           
 

Methods in cc.mallet.classify with parameters of type Instance
 Classification Winnow.classify(Instance instance)
          Classifies an instance using Winnow's weights
 Classification RankMaxEnt.classify(Instance instance)
           
 Classification PRAuxClassifier.classify(Instance instance)
           
 Classification NaiveBayes.classify(Instance instance)
          Classify an instance using NaiveBayes according to the trained data.
 Classification MCMaxEnt.classify(Instance instance)
           
 Classification MaxEnt.classify(Instance instance)
           
 Classification DecisionTree.classify(Instance instance)
           
 Classification ConfidencePredictingClassifier.classify(Instance instance)
           
 Classification ClassifierEnsemble.classify(Instance instance)
           
abstract  Classification Classifier.classify(Instance instance)
           
 Classification C45.classify(Instance instance)
           
 Classification BalancedWinnow.classify(Instance instance)
          Classifies an instance using BalancedWinnow's weights
 Classification BaggingClassifier.classify(Instance inst)
           
 Classification AdaBoostM2.classify(Instance inst)
           
 Classification AdaBoost.classify(Instance inst)
           
 Classification[] Classifier.classify(Instance[] instances)
           
 Classification AdaBoostM2.classify(Instance inst, int numWeakClassifiersToUse)
          Classify the given instance using only the first numWeakClassifiersToUse classifiers trained during boosting
 Classification AdaBoost.classify(Instance inst, int numWeakClassifiersToUse)
          Classify the given instance using only the first numWeakClassifiersToUse classifiers trained during boosting
 void PRAuxClassifier.getClassificationProbs(Instance instance, double[] scores)
           
 void RankMaxEnt.getClassificationScores(Instance instance, double[] scores)
           
 void PRAuxClassifier.getClassificationScores(Instance instance, double[] scores)
           
 void MCMaxEnt.getClassificationScores(Instance instance, double[] scores)
           
 void MaxEnt.getClassificationScores(Instance instance, double[] scores)
           
 void RankMaxEnt.getClassificationScoresForTies(Instance instance, double[] scores, int[] bestLabels)
          Used by RankMaxEntTrainer to calculate the value when the labeling contains ties.
 void MaxEnt.getClassificationScoresWithTemperature(Instance instance, double temperature, double[] scores)
           
 void RankMaxEnt.getUnnormalizedClassificationScores(Instance instance, double[] scores)
          returns unnormalized scores, corresponding to the score an element of the InstanceList being the "top" instance
 void MCMaxEnt.getUnnormalizedClassificationScores(Instance instance, double[] scores)
           
 void MaxEnt.getUnnormalizedClassificationScores(Instance instance, double[] scores)
           
 NaiveBayes NaiveBayesTrainer.trainIncremental(Instance instance)
           
 C ClassifierTrainer.ByInstanceIncrements.trainIncremental(Instance instanceToAdd)
           
 

Constructors in cc.mallet.classify with parameters of type Instance
Classification(Instance instance, Classifier classifier, Labeling labeling)
           
 

Uses of Instance in cc.mallet.cluster.iterator
 

Methods in cc.mallet.cluster.iterator that return Instance
 Instance PairSampleIterator.next()
           
 Instance NodeClusterSampleIterator.next()
           
 Instance ClusterSampleIterator.next()
           
 Instance AllPairsIterator.next()
           
 

Uses of Instance in cc.mallet.cluster.tui
 

Methods in cc.mallet.cluster.tui that return Instance
 Instance Clusterings2Clusterer.ClusteringPipe.pipe(Instance carrier)
           
 

Methods in cc.mallet.cluster.tui with parameters of type Instance
 Instance Clusterings2Clusterer.ClusteringPipe.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.cluster.util
 

Methods in cc.mallet.cluster.util with parameters of type Instance
static InstanceList ClusterUtils.makeList(Instance i, Instance j)
           
 

Uses of Instance in cc.mallet.extract
 

Method parameters in cc.mallet.extract with type arguments of type Instance
 Extraction Extractor.extract(java.util.Iterator<Instance> source)
          Performs extraction on a a set of raw documents.
 Extraction CRFExtractor.extract(java.util.Iterator<Instance> source)
           
 InstanceList CRFExtractor.pipeInstances(java.util.Iterator<Instance> source)
           
 

Uses of Instance in cc.mallet.extract.pipe
 

Methods in cc.mallet.extract.pipe that return Instance
 Instance TokenSequence2Tokenization.pipe(Instance carrier)
           
 

Methods in cc.mallet.extract.pipe with parameters of type Instance
 Instance TokenSequence2Tokenization.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.fst
 

Methods in cc.mallet.fst that return Instance
 Instance Transducer.label(Instance instance)
          Take input sequence from instance.data and put the output sequence in instance.target.
 Instance SimpleTagger.SimpleTaggerSentence2FeatureVectorSequence.pipe(Instance carrier)
           
 Instance Transducer.transduce(Instance instance)
          Take input sequence from instance.data and put the output sequence in instance.data.
 

Methods in cc.mallet.fst with parameters of type Instance
 Instance Transducer.label(Instance instance)
          Take input sequence from instance.data and put the output sequence in instance.target.
 Instance SimpleTagger.SimpleTaggerSentence2FeatureVectorSequence.pipe(Instance carrier)
           
abstract  boolean TransducerTrainer.ByInstanceIncrements.trainIncremental(Instance trainingInstance)
           
 boolean CRFTrainerByStochasticGradient.trainIncremental(Instance trainingInstance)
           
 double CRFTrainerByStochasticGradient.trainIncrementalLikelihood(Instance trainingInstance)
          Adjust the parameters by default learning rate according to the gradient of this single Instance, and return the true label sequence likelihood.
 double CRFTrainerByStochasticGradient.trainIncrementalLikelihood(Instance trainingInstance, double rate)
          Adjust the parameters by learning rate according to the gradient of this single Instance, and return the true label sequence likelihood.
 Instance Transducer.transduce(Instance instance)
          Take input sequence from instance.data and put the output sequence in instance.data.
 

Uses of Instance in cc.mallet.fst.confidence
 

Methods in cc.mallet.fst.confidence that return Instance
 Instance SequenceConfidenceInstance.getInstance()
           
 Instance PipedInstanceWithConfidence.getInstance()
           
 Instance InstanceWithConfidence.getInstance()
           
 

Methods in cc.mallet.fst.confidence with parameters of type Instance
 double ViterbiRatioConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of an Instance.
 double ViterbiConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of a Instance.
abstract  double TransducerSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of a Sequence.
 double SegmentProductConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of a Instance.
 double RandomSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of an Instance.
 double QBCSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of a Instance.
 double NBestViterbiConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of a Instance.
 double MinSegmentConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of a Instance.
 double MaxEntSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)
          Calculates the confidence in the tagging of an Instance.
 Segment[] TransducerConfidenceEstimator.rankSegmentsByConfidence(Instance instance, java.lang.Object[] startTags, java.lang.Object[] continueTags)
          ranks the segments in one Instance
 

Constructors in cc.mallet.fst.confidence with parameters of type Instance
InstanceWithConfidence(Instance inst, double c, boolean correct)
           
InstanceWithConfidence(Instance inst, double c, Sequence predicted)
           
PipedInstanceWithConfidence(Instance inst, double c, boolean correct)
           
SequenceConfidenceInstance(Instance inst)
           
 

Uses of Instance in cc.mallet.fst.tests
 

Methods in cc.mallet.fst.tests that return Instance
 Instance TestMEMM.TestMEMMTokenSequenceRemoveSpaces.pipe(Instance carrier)
           
 Instance TestMEMM.TestMEMM2String.pipe(Instance carrier)
           
 Instance TestCRF.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier)
           
 Instance TestCRF.TestCRF2String.pipe(Instance carrier)
           
 

Methods in cc.mallet.fst.tests with parameters of type Instance
 Instance TestMEMM.TestMEMMTokenSequenceRemoveSpaces.pipe(Instance carrier)
           
 Instance TestMEMM.TestMEMM2String.pipe(Instance carrier)
           
 Instance TestCRF.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier)
           
 Instance TestCRF.TestCRF2String.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.grmm.learning
 

Methods in cc.mallet.grmm.learning that return Instance
 Instance GenericAcrfData2TokenSequence.pipe(Instance carrier)
           
 

Methods in cc.mallet.grmm.learning with parameters of type Instance
abstract  void ACRF.Template.addInstantiatedCliques(ACRF.UnrolledGraph graph, Instance instance)
          Adds all instiated cliques for an instance.
 void ACRF.SequenceTemplate.addInstantiatedCliques(ACRF.UnrolledGraph graph, Instance instance)
           
 Assignment ACRF.bestAssignment(Instance inst)
           
 LabelsSequence ACRF.getBestLabels(Instance inst)
           
 Instance GenericAcrfData2TokenSequence.pipe(Instance carrier)
           
 void ACRF.GraphPostProcessor.process(ACRF.UnrolledGraph graph, Instance inst)
           
 ACRF.UnrolledGraph ACRF.unroll(Instance inst)
           
 ACRF.UnrolledGraph ACRF.unrollStructureOnly(Instance inst)
           
 

Constructors in cc.mallet.grmm.learning with parameters of type Instance
ACRF.UnrolledGraph(Instance inst, ACRF.Template[] templates, ACRF.Template[] fixed)
           
ACRF.UnrolledGraph(Instance inst, ACRF.Template[] templates, java.util.List fixed, boolean setupPotentials)
          Creates a graphical model for a given instance.
 

Uses of Instance in cc.mallet.grmm.learning.extract
 

Method parameters in cc.mallet.grmm.learning.extract with type arguments of type Instance
 Extraction ACRFExtractor.extract(java.util.Iterator<Instance> source)
           
 ACRFExtractorTrainer ACRFExtractorTrainer.setDataSource(java.util.Iterator<Instance> trainIterator, java.util.Iterator<Instance> testIterator)
           
 ACRFExtractorTrainer ACRFExtractorTrainer.setDataSource(java.util.Iterator<Instance> trainIterator, java.util.Iterator<Instance> testIterator)
           
 

Uses of Instance in cc.mallet.grmm.util
 

Methods in cc.mallet.grmm.util that return Instance
 Instance PipedIterator.next()
          Deprecated.  
 Instance SliceLabelsSequence.pipe(Instance carrier)
           
 Instance RememberTokenizationPipe.pipe(Instance carrier)
           
 Instance LabelsSequence2Assignment.pipe(Instance carrier)
           
 

Methods in cc.mallet.grmm.util with parameters of type Instance
 Instance SliceLabelsSequence.pipe(Instance carrier)
           
 Instance RememberTokenizationPipe.pipe(Instance carrier)
           
 Instance LabelsSequence2Assignment.pipe(Instance carrier)
           
 

Constructor parameters in cc.mallet.grmm.util with type arguments of type Instance
PipedIterator(java.util.Iterator<Instance> subIt, Pipe pipe)
          Deprecated.  
 

Uses of Instance in cc.mallet.pipe
 

Methods in cc.mallet.pipe that return Instance
 Instance Pipe.instanceFrom(Instance inst)
           
 Instance[] Pipe.instancesFrom(Instance inst)
           
 Instance[] Pipe.instancesFrom(java.util.Iterator<Instance> source)
          A convenience method that will pull all instances from source through this pipe, and return the results as an array.
 Instance TokenSequenceRemoveStopwords.pipe(Instance carrier)
           
 Instance TokenSequenceRemoveNonAlpha.pipe(Instance carrier)
           
 Instance TokenSequenceParseFeatureString.pipe(Instance carrier)
           
 Instance TokenSequenceNGrams.pipe(Instance carrier)
           
 Instance TokenSequenceMatchDataAndTarget.pipe(Instance carrier)
           
 Instance TokenSequenceLowercase.pipe(Instance carrier)
           
 Instance TokenSequence2FeatureVectorSequence.pipe(Instance carrier)
           
 Instance TokenSequence2FeatureSequenceWithBigrams.pipe(Instance carrier)
           
 Instance TokenSequence2FeatureSequence.pipe(Instance carrier)
           
 Instance Token2FeatureVector.pipe(Instance carrier)
           
 Instance TargetStringToFeatures.pipe(Instance carrier)
           
 Instance TargetRememberLastLabel.pipe(Instance carrier)
           
 Instance Target2LabelSequence.pipe(Instance carrier)
           
 Instance Target2Label.pipe(Instance carrier)
           
 Instance Target2FeatureSequence.pipe(Instance carrier)
           
 Instance SvmLight2FeatureVectorAndLabel.pipe(Instance carrier)
           
 Instance StringList2FeatureSequence.pipe(Instance carrier)
           
 Instance StringAddNewLineDelimiter.pipe(Instance carrier)
           
 Instance SourceLocation2TokenSequence.pipe(Instance carrier)
           
 Instance SimpleTokenizer.pipe(Instance instance)
           
 Instance SimpleTaggerSentence2TokenSequence.pipe(Instance carrier)
          Takes an instance with data of type String or String[][] and creates an Instance of type TokenSequence.
 Instance SimpleTaggerSentence2StringTokenization.pipe(Instance carrier)
          Takes an instance with data of type String or String[][] and creates an Instance of type StringTokenization.
 Instance SGML2TokenSequence.pipe(Instance carrier)
           
 Instance SelectiveSGML2TokenSequence.pipe(Instance carrier)
           
 Instance SaveDataInSource.pipe(Instance carrier)
           
 Instance PrintTokenSequenceFeatures.pipe(Instance carrier)
           
 Instance PrintInputAndTarget.pipe(Instance carrier)
           
 Instance PrintInput.pipe(Instance carrier)
           
 Instance Pipe.pipe(Instance inst)
          Really this should be 'protected', but isn't for historical reasons.
 Instance Noop.pipe(Instance carrier)
           
 Instance MakeAmpersandXMLFriendly.pipe(Instance carrier)
           
 Instance LineGroupString2TokenSequence.pipe(Instance carrier)
           
 Instance InstanceListTrimFeaturesByCount.pipe(Instance carrier)
           
 Instance Input2CharSequence.pipe(Instance carrier)
           
 Instance Filename2CharSequence.pipe(Instance carrier)
           
 Instance FeatureVectorConjunctions.pipe(Instance carrier)
           
 Instance FeatureValueString2FeatureVector.pipe(Instance carrier)
           
 Instance FeatureSequenceConvolution.pipe(Instance carrier)
          construct word co-occurrence features from the original sequence do combinatoric, n choose 2, can be extended to n choose 3 public void convolution() { int fi = -1; int pre = -1; int i,j; int curLen = length; for(i = 0; i < curLen-1; i++) { for(j = i + 1; j < curLen; j++) { pre = features[i]; fi = features[j]; Object preO = dictionary.lookupObject(pre); Object curO = dictionary.lookupObject(fi); Object coO = preO.toString() + "_" + curO.toString(); add(coO); } } }
 Instance FeatureSequence2FeatureVector.pipe(Instance carrier)
           
 Instance FeatureSequence2AugmentableFeatureVector.pipe(Instance carrier)
           
 Instance FeatureDocFreqPipe.pipe(Instance instance)
           
 Instance FeatureCountPipe.pipe(Instance instance)
           
 Instance Directory2FileIterator.pipe(Instance carrier)
           
 Instance Csv2FeatureVector.pipe(Instance carrier)
          Convert the data in the given Instance from a CharSequence of sparse feature-value pairs to a FeatureVector
 Instance Csv2Array.pipe(Instance carrier)
          Convert the data in an Instance from a CharSequence of comma-separated-values to an array, where each index is the feature name.
 Instance Classification2ConfidencePredictingFeatureVector.pipe(Instance carrier)
           
 Instance CharSubsequence.pipe(Instance carrier)
           
 Instance CharSequenceReplace.pipe(Instance carrier)
           
 Instance CharSequenceRemoveUUEncodedBlocks.pipe(Instance carrier)
           
 Instance CharSequenceRemoveHTML.pipe(Instance carrier)
           
 Instance CharSequenceLowercase.pipe(Instance carrier)
           
 Instance CharSequenceArray2TokenSequence.pipe(Instance carrier)
           
 Instance CharSequence2TokenSequence.pipe(Instance carrier)
           
 Instance CharSequence2CharNGrams.pipe(Instance carrier)
           
 Instance AugmentableFeatureVectorLogScale.pipe(Instance carrier)
           
 Instance AugmentableFeatureVectorAddConjunctions.pipe(Instance carrier)
           
 Instance Array2FeatureVector.pipe(Instance carrier)
          Convert the data in an Instance from an array to a FeatureVector leaving other fields unchanged.
 Instance AddClassifierTokenPredictions.pipe(Instance carrier)
          Add the token classifier's predictions as features to the instance.
 

Methods in cc.mallet.pipe that return types with arguments of type Instance
 java.util.Iterator<Instance> TokenSequence2TokenInstances.newIteratorFrom(java.util.Iterator<Instance> source)
           
 java.util.Iterator<Instance> SerialPipes.newIteratorFrom(java.util.Iterator<Instance> source)
           
 java.util.Iterator<Instance> Pipe.newIteratorFrom(java.util.Iterator<Instance> source)
          Given an InstanceIterator, return a new InstanceIterator whose instances have also been processed by this pipe.
 java.util.Iterator<Instance> FilterEmptyFeatureVectors.newIteratorFrom(java.util.Iterator<Instance> source)
           
 java.util.Iterator<Instance> FeatureVectorSequence2FeatureVectors.newIteratorFrom(java.util.Iterator<Instance> inputIterator)
           
 java.util.Iterator<Instance> BranchingPipe.newIteratorFrom(java.util.Iterator<Instance> source)
          Deprecated.  
 

Methods in cc.mallet.pipe with parameters of type Instance
 Classification AddClassifierTokenPredictions.TokenClassifiers.classify(Instance instance)
           
 Classification AddClassifierTokenPredictions.TokenClassifiers.classify(Instance instance, boolean useOutOfFold)
           
static InstanceList AddClassifierTokenPredictions.convert(Instance inst, Noop alphabetsPipe)
           
 Instance Pipe.instanceFrom(Instance inst)
           
 Instance[] Pipe.instancesFrom(Instance inst)
           
 Instance TokenSequenceRemoveStopwords.pipe(Instance carrier)
           
 Instance TokenSequenceRemoveNonAlpha.pipe(Instance carrier)
           
 Instance TokenSequenceParseFeatureString.pipe(Instance carrier)
           
 Instance TokenSequenceNGrams.pipe(Instance carrier)
           
 Instance TokenSequenceMatchDataAndTarget.pipe(Instance carrier)
           
 Instance TokenSequenceLowercase.pipe(Instance carrier)
           
 Instance TokenSequence2FeatureVectorSequence.pipe(Instance carrier)
           
 Instance TokenSequence2FeatureSequenceWithBigrams.pipe(Instance carrier)
           
 Instance TokenSequence2FeatureSequence.pipe(Instance carrier)
           
 Instance Token2FeatureVector.pipe(Instance carrier)
           
 Instance TargetStringToFeatures.pipe(Instance carrier)
           
 Instance TargetRememberLastLabel.pipe(Instance carrier)
           
 Instance Target2LabelSequence.pipe(Instance carrier)
           
 Instance Target2Label.pipe(Instance carrier)
           
 Instance Target2FeatureSequence.pipe(Instance carrier)
           
 Instance SvmLight2FeatureVectorAndLabel.pipe(Instance carrier)
           
 Instance StringList2FeatureSequence.pipe(Instance carrier)
           
 Instance StringAddNewLineDelimiter.pipe(Instance carrier)
           
 Instance SourceLocation2TokenSequence.pipe(Instance carrier)
           
 Instance SimpleTokenizer.pipe(Instance instance)
           
 Instance SimpleTaggerSentence2TokenSequence.pipe(Instance carrier)
          Takes an instance with data of type String or String[][] and creates an Instance of type TokenSequence.
 Instance SimpleTaggerSentence2StringTokenization.pipe(Instance carrier)
          Takes an instance with data of type String or String[][] and creates an Instance of type StringTokenization.
 Instance SGML2TokenSequence.pipe(Instance carrier)
           
 Instance SelectiveSGML2TokenSequence.pipe(Instance carrier)
           
 Instance SaveDataInSource.pipe(Instance carrier)
           
 Instance PrintTokenSequenceFeatures.pipe(Instance carrier)
           
 Instance PrintInputAndTarget.pipe(Instance carrier)
           
 Instance PrintInput.pipe(Instance carrier)
           
 Instance Pipe.pipe(Instance inst)
          Really this should be 'protected', but isn't for historical reasons.
 Instance Noop.pipe(Instance carrier)
           
 Instance MakeAmpersandXMLFriendly.pipe(Instance carrier)
           
 Instance LineGroupString2TokenSequence.pipe(Instance carrier)
           
 Instance InstanceListTrimFeaturesByCount.pipe(Instance carrier)
           
 Instance Input2CharSequence.pipe(Instance carrier)
           
 Instance Filename2CharSequence.pipe(Instance carrier)
           
 Instance FeatureVectorConjunctions.pipe(Instance carrier)
           
 Instance FeatureValueString2FeatureVector.pipe(Instance carrier)
           
 Instance FeatureSequenceConvolution.pipe(Instance carrier)
          construct word co-occurrence features from the original sequence do combinatoric, n choose 2, can be extended to n choose 3 public void convolution() { int fi = -1; int pre = -1; int i,j; int curLen = length; for(i = 0; i < curLen-1; i++) { for(j = i + 1; j < curLen; j++) { pre = features[i]; fi = features[j]; Object preO = dictionary.lookupObject(pre); Object curO = dictionary.lookupObject(fi); Object coO = preO.toString() + "_" + curO.toString(); add(coO); } } }
 Instance FeatureSequence2FeatureVector.pipe(Instance carrier)
           
 Instance FeatureSequence2AugmentableFeatureVector.pipe(Instance carrier)
           
 Instance FeatureDocFreqPipe.pipe(Instance instance)
           
 Instance FeatureCountPipe.pipe(Instance instance)
           
 Instance Directory2FileIterator.pipe(Instance carrier)
           
 Instance Csv2FeatureVector.pipe(Instance carrier)
          Convert the data in the given Instance from a CharSequence of sparse feature-value pairs to a FeatureVector
 Instance Csv2Array.pipe(Instance carrier)
          Convert the data in an Instance from a CharSequence of comma-separated-values to an array, where each index is the feature name.
 Instance Classification2ConfidencePredictingFeatureVector.pipe(Instance carrier)
           
 Instance CharSubsequence.pipe(Instance carrier)
           
 Instance CharSequenceReplace.pipe(Instance carrier)
           
 Instance CharSequenceRemoveUUEncodedBlocks.pipe(Instance carrier)
           
 Instance CharSequenceRemoveHTML.pipe(Instance carrier)
           
 Instance CharSequenceLowercase.pipe(Instance carrier)
           
 Instance CharSequenceArray2TokenSequence.pipe(Instance carrier)
           
 Instance CharSequence2TokenSequence.pipe(Instance carrier)
           
 Instance CharSequence2CharNGrams.pipe(Instance carrier)
           
 Instance AugmentableFeatureVectorLogScale.pipe(Instance carrier)
           
 Instance AugmentableFeatureVectorAddConjunctions.pipe(Instance carrier)
           
 Instance Array2FeatureVector.pipe(Instance carrier)
          Convert the data in an Instance from an array to a FeatureVector leaving other fields unchanged.
 Instance AddClassifierTokenPredictions.pipe(Instance carrier)
          Add the token classifier's predictions as features to the instance.
 boolean Pipe.precondition(Instance inst)
          Each instance processed is tested by this method.
 

Method parameters in cc.mallet.pipe with type arguments of type Instance
 Instance[] Pipe.instancesFrom(java.util.Iterator<Instance> source)
          A convenience method that will pull all instances from source through this pipe, and return the results as an array.
 java.util.Iterator<Instance> TokenSequence2TokenInstances.newIteratorFrom(java.util.Iterator<Instance> source)
           
 java.util.Iterator<Instance> SerialPipes.newIteratorFrom(java.util.Iterator<Instance> source)
           
 java.util.Iterator<Instance> Pipe.newIteratorFrom(java.util.Iterator<Instance> source)
          Given an InstanceIterator, return a new InstanceIterator whose instances have also been processed by this pipe.
 java.util.Iterator<Instance> FilterEmptyFeatureVectors.newIteratorFrom(java.util.Iterator<Instance> source)
           
 java.util.Iterator<Instance> FeatureVectorSequence2FeatureVectors.newIteratorFrom(java.util.Iterator<Instance> inputIterator)
           
 java.util.Iterator<Instance> BranchingPipe.newIteratorFrom(java.util.Iterator<Instance> source)
          Deprecated.  
 

Uses of Instance in cc.mallet.pipe.iterator
 

Methods in cc.mallet.pipe.iterator that return Instance
 Instance UnlabeledFileIterator.next()
           
 Instance StringArrayIterator.next()
           
 Instance SimpleFileLineIterator.next()
           
 Instance SelectiveFileLineIterator.next()
           
 Instance SegmentIterator.next()
           
 Instance RandomTokenSequenceIterator.next()
           
 Instance RandomFeatureVectorIterator.next()
           
abstract  Instance PipeInputIterator.next()
          Deprecated.  
 Instance PipeExtendedIterator.next()
          Deprecated.  
 Instance PatternMatchIterator.next()
           
 Instance ParenGroupIterator.next()
           
 Instance LineIterator.next()
           
 Instance LineGroupIterator.next()
           
 Instance FileUriIterator.next()
           
 Instance FileListIterator.next()
           
 Instance FileIterator.next()
           
 Instance EmptyInstanceIterator.next()
           
 Instance CsvIterator.next()
           
 Instance ConcatenatedInstanceIterator.next()
           
 Instance ArrayIterator.next()
           
 Instance ArrayDataAndTargetIterator.next()
           
 

Constructors in cc.mallet.pipe.iterator with parameters of type Instance
SegmentIterator(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags, Sequence prediction)
          Iterate over segments in one instance.
SegmentIterator(Transducer model, Instance instance, java.lang.Object[] segmentStartTags, java.lang.Object[] segmentContinueTags)
          Iterates over Segments for only one Instance.
 

Constructor parameters in cc.mallet.pipe.iterator with type arguments of type Instance
PipeExtendedIterator(java.util.Iterator<Instance> iterator, Pipe pipe)
          Deprecated. Creates a new PipeExtendedIterator instance.
 

Uses of Instance in cc.mallet.pipe.tests
 

Methods in cc.mallet.pipe.tests that return Instance
 Instance TestSGML2TokenSequence.Array2ArrayIterator.pipe(Instance carrier)
           
 Instance TestInstancePipe.Array2ArrayIterator.pipe(Instance carrier)
           
 

Methods in cc.mallet.pipe.tests with parameters of type Instance
 Instance TestSGML2TokenSequence.Array2ArrayIterator.pipe(Instance carrier)
           
 Instance TestInstancePipe.Array2ArrayIterator.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.pipe.tsf
 

Methods in cc.mallet.pipe.tsf that return Instance
 Instance TrieLexiconMembership.pipe(Instance carrier)
           
 Instance TokenTextNGrams.pipe(Instance carrier)
           
 Instance TokenTextCharSuffix.pipe(Instance carrier)
           
 Instance TokenTextCharPrefix.pipe(Instance carrier)
           
 Instance TokenTextCharNGrams.pipe(Instance carrier)
           
 Instance TokenText.pipe(Instance carrier)
           
 Instance TokenFirstPosition.pipe(Instance instance)
           
 Instance Target2BIOFormat.pipe(Instance carrier)
           
 Instance SequencePrintingPipe.pipe(Instance carrier)
           
 Instance RegexMatches.pipe(Instance carrier)
           
 Instance OffsetPropertyConjunctions.pipe(Instance carrier)
           
 Instance OffsetFeatureConjunction.pipe(Instance carrier)
           
 Instance OffsetConjunctions.pipe(Instance carrier)
           
 Instance LexiconMembership.pipe(Instance carrier)
           
 Instance FeaturesOfFirstMention.pipe(Instance carrier)
           
 Instance FeaturesInWindow.pipe(Instance carrier)
           
 Instance CountMatchesMatching.pipe(Instance carrier)
           
 Instance CountMatchesAlignedWithOffsets.pipe(Instance carrier)
           
 Instance CountMatches.pipe(Instance carrier)
           
 

Methods in cc.mallet.pipe.tsf with parameters of type Instance
 Instance TrieLexiconMembership.pipe(Instance carrier)
           
 Instance TokenTextNGrams.pipe(Instance carrier)
           
 Instance TokenTextCharSuffix.pipe(Instance carrier)
           
 Instance TokenTextCharPrefix.pipe(Instance carrier)
           
 Instance TokenTextCharNGrams.pipe(Instance carrier)
           
 Instance TokenText.pipe(Instance carrier)
           
 Instance TokenFirstPosition.pipe(Instance instance)
           
 Instance Target2BIOFormat.pipe(Instance carrier)
           
 Instance SequencePrintingPipe.pipe(Instance carrier)
           
 Instance RegexMatches.pipe(Instance carrier)
           
 Instance OffsetPropertyConjunctions.pipe(Instance carrier)
           
 Instance OffsetFeatureConjunction.pipe(Instance carrier)
           
 Instance OffsetConjunctions.pipe(Instance carrier)
           
 Instance LexiconMembership.pipe(Instance carrier)
           
 Instance FeaturesOfFirstMention.pipe(Instance carrier)
           
 Instance FeaturesInWindow.pipe(Instance carrier)
           
 Instance CountMatchesMatching.pipe(Instance carrier)
           
 Instance CountMatchesAlignedWithOffsets.pipe(Instance carrier)
           
 Instance CountMatches.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.share.casutton.ner
 

Methods in cc.mallet.share.casutton.ner that return Instance
 Instance ConllNer2003Sentence2TokenSequence.pipe(Instance carrier)
           
 

Methods in cc.mallet.share.casutton.ner with parameters of type Instance
 Instance ConllNer2003Sentence2TokenSequence.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.share.mccallum.ner
 

Methods in cc.mallet.share.mccallum.ner that return Instance
 Instance TokenSequenceDocHeader.pipe(Instance carrier)
           
 Instance ConllNer2003Sentence2TokenSequence.pipe(Instance carrier)
           
 

Methods in cc.mallet.share.mccallum.ner with parameters of type Instance
 Instance TokenSequenceDocHeader.pipe(Instance carrier)
           
 Instance ConllNer2003Sentence2TokenSequence.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.share.upenn
 

Method parameters in cc.mallet.share.upenn with type arguments of type Instance
static Classification[] MaxEntShell.classify(Classifier classifier, java.util.Iterator<Instance> data)
          Compute the maxent classifications for unlabeled instances given by an iterator.
static double MaxEntShell.test(Classifier classifier, java.util.Iterator<Instance> data)
          Test a maxent classifier.
static Classifier MaxEntShell.train(java.util.Iterator<Instance> data, double var, java.io.File save)
          Train a maxent classifier.
 

Uses of Instance in cc.mallet.share.upenn.ner
 

Methods in cc.mallet.share.upenn.ner that return Instance
 Instance LongRegexMatches.pipe(Instance carrier)
           
 Instance ListMember.pipe(Instance carrier)
           
 Instance LengthBins.pipe(Instance carrier)
           
 Instance FeatureWindow.pipe(Instance carrier)
           
 

Methods in cc.mallet.share.upenn.ner with parameters of type Instance
 Instance LongRegexMatches.pipe(Instance carrier)
           
 Instance ListMember.pipe(Instance carrier)
           
 Instance LengthBins.pipe(Instance carrier)
           
 Instance FeatureWindow.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.share.weili.ner.enron
 

Methods in cc.mallet.share.weili.ner.enron that return Instance
 Instance EnronMessage2TokenSequence.pipe(Instance carrier)
           
 

Methods in cc.mallet.share.weili.ner.enron with parameters of type Instance
 Instance EnronMessage2TokenSequence.pipe(Instance carrier)
           
 

Uses of Instance in cc.mallet.topics
 

Fields in cc.mallet.topics declared as Instance
 Instance TopicAssignment.instance
           
 Instance LDAHyper.Topication.instance
           
 Instance[] PolylingualTopicModel.TopicAssignment.instances
           
 

Methods in cc.mallet.topics with parameters of type Instance
 double[] TopicInferencer.getSampledDistribution(Instance instance, int numIterations, int thinning, int burnIn)
          Use Gibbs sampling to infer a topic distribution.
protected  int LDAHyper.instanceLength(Instance instance)
          Deprecated.  
 void DMRTopicModel.setAlphas(Instance instance)
          Set alpha based on features in an instance
 

Constructors in cc.mallet.topics with parameters of type Instance
LDAHyper.Topication(Instance instance, LDAHyper model, LabelSequence topicSequence)
           
PolylingualTopicModel.TopicAssignment(Instance[] instances, LabelSequence[] topicSequences)
           
TopicAssignment(Instance instance, LabelSequence topicSequence)
           
 

Uses of Instance in cc.mallet.types
 

Methods in cc.mallet.types that return Instance
 Instance PagedInstanceList.get(int index)
          Returns the Instance at the specified index.
 Instance MultiInstanceList.get(int index)
           
 Instance SingleInstanceIterator.next()
           
abstract  Instance ChainedInstanceIterator.next()
          Deprecated.  
 Instance MultiInstanceList.remove(int index)
           
 Instance InstanceList.remove(int index)
           
 Instance PagedInstanceList.set(int index, Instance instance)
          Replaces the Instance at position index with a new one.
 Instance MultiInstanceList.set(int index, Instance instance)
           
 Instance InstanceList.set(int index, Instance instance)
           
 Instance Instance.shallowCopy()
           
 

Methods in cc.mallet.types that return types with arguments of type Instance
 java.util.Iterator<Instance> MultiInstanceList.iterator()
           
 java.util.ListIterator<Instance> MultiInstanceList.listIterator()
           
 java.util.ListIterator<Instance> MultiInstanceList.listIterator(int index)
           
 

Methods in cc.mallet.types with parameters of type Instance
 boolean PagedInstanceList.add(Instance instance)
          Appends the instance to this list.
 boolean MultiInstanceList.add(Instance instance)
           
 boolean InstanceList.add(Instance instance)
          Appends the instance to this list without passing the instance through the InstanceList's pipe.
 boolean MultiInstanceList.add(Instance instance, double instanceWeight)
           
 boolean InstanceList.add(Instance instance, double instanceWeight)
          Appends the instance to this list without passing it through this InstanceList's pipe, assigning it the specified weight.
 void MultiInstanceList.add(int index, Instance element)
           
 void InstanceList.add(int index, Instance element)
           
 void InstanceList.addThruPipe(Instance inst)
          Adds the input instance to this list, after passing it through the InstanceList's pipe.
 double InstanceList.getInstanceWeight(Instance instance)
           
 boolean Labeler.label(Instance instanceToLabel)
          Given the (presumably unlabeled) instanceToLabel, set its target field to the true label.
 boolean MultiInstanceList.remove(Instance instance)
           
 boolean InstanceList.remove(Instance instance)
           
 Instance PagedInstanceList.set(int index, Instance instance)
          Replaces the Instance at position index with a new one.
 Instance MultiInstanceList.set(int index, Instance instance)
           
 Instance InstanceList.set(int index, Instance instance)
           
 void MultiInstanceList.setInstance(int index, Instance instance)
           
 void InstanceList.setInstance(int index, Instance instance)
          Replaces the Instance at position index with a new one.
 void MultiInstanceList.setInstanceWeight(Instance instance, double weight)
           
 void InstanceList.setInstanceWeight(Instance instance, double weight)
           
 

Method parameters in cc.mallet.types with type arguments of type Instance
 boolean InstanceList.addAll(java.util.Collection<? extends Instance> instances)
           
 boolean InstanceList.addAll(int index, java.util.Collection<? extends Instance> c)
           
 void InstanceList.addThruPipe(java.util.Iterator<Instance> ii)
          Adds to this list every instance generated by the iterator, passing each one through this InstanceList's pipe.
 boolean ChainedInstanceIterator.sourceNowHasNext(java.util.Iterator<Instance> source)
          Deprecated. The "source" of this iterator sends this message to tell this iterator that, even though source.hasNext() may have returned false before, it would now return true.
 

Constructors in cc.mallet.types with parameters of type Instance
SingleInstanceIterator(Instance inst)
           
 

Constructor parameters in cc.mallet.types with type arguments of type Instance
ChainedInstanceIterator(java.util.Iterator<Instance> source, ChainedInstanceIterator target)
          Deprecated. Both source and target may be null.
 

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