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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` | `MaxEnt.classify(Instance instance)`
`Classification` | `ClassifierEnsemble.classify(Instance instance)`
`Classification` | `Winnow.classify(Instance instance)` Classifies an instance using Winnow's weights
`Classification` | `RankMaxEnt.classify(Instance instance)`
`Classification` | `AdaBoostM2.classify(Instance inst)`
`Classification` | `AdaBoost.classify(Instance inst)`
`Classification` | `BalancedWinnow.classify(Instance instance)` Classifies an instance using BalancedWinnow's weights
`Classification` | `ConfidencePredictingClassifier.classify(Instance instance)`
`Classification` | `BaggingClassifier.classify(Instance inst)`
`Classification` | `C45.classify(Instance instance)`
`Classification` | `DecisionTree.classify(Instance instance)`
`Classification` | `NaiveBayes.classify(Instance instance)` Classify an instance using NaiveBayes according to the trained data.
`Classification` | `MCMaxEnt.classify(Instance instance)`
`abstract Classification` | `Classifier.classify(Instance instance)`
`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` | `MaxEnt.getClassificationScores(Instance instance, double[] scores)`
`void` | `RankMaxEnt.getClassificationScores(Instance instance, double[] scores)`
`void` | `MCMaxEnt.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` | `MaxEnt.getUnnormalizedClassificationScores(Instance instance, 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)`
`C` | `ClassifierTrainer.ByInstanceIncrements.trainIncremental(Instance instanceToAdd)`
`NaiveBayes` | `NaiveBayesTrainer.trainIncremental(Instance instance)`

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` | `CRFExtractor.extract(java.util.Iterator<Instance> source)`
`Extraction` | `Extractor.extract(java.util.Iterator<Instance> source)` Performs extraction on a a set of raw documents.
`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)`
`boolean` | `CRFTrainerByStochasticGradient.trainIncremental(Instance trainingInstance)`
`abstract boolean` | `TransducerTrainer.ByInstanceIncrements.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` | `InstanceWithConfidence.getInstance()`
`Instance` | `PipedInstanceWithConfidence.getInstance()`

Methods in cc.mallet.fst.confidence with parameters of type Instance
`double` | `ViterbiConfidenceEstimator.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`.
`abstract double` | `TransducerSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)` Calculates the confidence in the tagging of a `Sequence`.
`double` | `NBestViterbiConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)` Calculates the confidence in the tagging of a `Instance`.
`double` | `SegmentProductConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)` Calculates the confidence in the tagging of a `Instance`.
`double` | `ViterbiRatioConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)` Calculates the confidence in the tagging of an `Instance`.
`double` | `MinSegmentConfidenceEstimator.estimateConfidenceFor(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags)` Calculates the confidence in the tagging of a `Instance`.
`double` | `QBCSequenceConfidenceEstimator.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` | `TestCRF.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier)`
`Instance` | `TestCRF.TestCRF2String.pipe(Instance carrier)`
`Instance` | `TestMEMM.TestMEMMTokenSequenceRemoveSpaces.pipe(Instance carrier)`
`Instance` | `TestMEMM.TestMEMM2String.pipe(Instance carrier)`

Methods in cc.mallet.fst.tests with parameters of type Instance
`Instance` | `TestCRF.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier)`
`Instance` | `TestCRF.TestCRF2String.pipe(Instance carrier)`
`Instance` | `TestMEMM.TestMEMMTokenSequenceRemoveSpaces.pipe(Instance carrier)`
`Instance` | `TestMEMM.TestMEMM2String.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` | `RememberTokenizationPipe.pipe(Instance carrier)`
`Instance` | `SliceLabelsSequence.pipe(Instance carrier)`
`Instance` | `LabelsSequence2Assignment.pipe(Instance carrier)`

Methods in cc.mallet.grmm.util with parameters of type Instance
`Instance` | `RememberTokenizationPipe.pipe(Instance carrier)`
`Instance` | `SliceLabelsSequence.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` | `TokenSequenceRemoveNonAlpha.pipe(Instance carrier)`
`Instance` | `SimpleTaggerSentence2StringTokenization.pipe(Instance carrier)` Takes an instance with data of type String or String[][] and creates an Instance of type StringTokenization.
`Instance` | `Input2CharSequence.pipe(Instance carrier)`
`Instance` | `SGML2TokenSequence.pipe(Instance carrier)`
`Instance` | `FeatureSequence2AugmentableFeatureVector.pipe(Instance carrier)`
`Instance` | `MakeAmpersandXMLFriendly.pipe(Instance carrier)`
`Instance` | `AugmentableFeatureVectorAddConjunctions.pipe(Instance carrier)`
`Instance` | `TokenSequenceLowercase.pipe(Instance carrier)`
`Instance` | `CharSequenceReplace.pipe(Instance carrier)`
`Instance` | `SourceLocation2TokenSequence.pipe(Instance carrier)`
`Instance` | `PrintInput.pipe(Instance carrier)`
`Instance` | `CharSequenceArray2TokenSequence.pipe(Instance carrier)`
`Instance` | `Pipe.pipe(Instance inst)` Really this should be 'protected', but isn't for historical reasons.
`Instance` | `Target2Label.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` | `Directory2FileIterator.pipe(Instance carrier)`
`Instance` | `TargetRememberLastLabel.pipe(Instance carrier)`
`Instance` | `CharSequenceLowercase.pipe(Instance carrier)`
`Instance` | `FeatureSequence2FeatureVector.pipe(Instance carrier)`
`Instance` | `CharSubsequence.pipe(Instance carrier)`
`Instance` | `TokenSequenceNGrams.pipe(Instance carrier)`
`Instance` | `CharSequenceRemoveUUEncodedBlocks.pipe(Instance carrier)`
`Instance` | `FeatureCountPipe.pipe(Instance instance)`
`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` | `CharSequenceRemoveHTML.pipe(Instance carrier)`
`Instance` | `SaveDataInSource.pipe(Instance carrier)`
`Instance` | `FeatureValueString2FeatureVector.pipe(Instance carrier)`
`Instance` | `InstanceListTrimFeaturesByCount.pipe(Instance carrier)`
`Instance` | `TokenSequence2FeatureSequenceWithBigrams.pipe(Instance carrier)`
`Instance` | `LineGroupString2TokenSequence.pipe(Instance carrier)`
`Instance` | `TokenSequence2FeatureVectorSequence.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` | `PrintInputAndTarget.pipe(Instance carrier)`
`Instance` | `SvmLight2FeatureVectorAndLabel.pipe(Instance carrier)`
`Instance` | `AddClassifierTokenPredictions.pipe(Instance carrier)` Add the token classifier's predictions as features to the instance.
`Instance` | `StringAddNewLineDelimiter.pipe(Instance carrier)`
`Instance` | `Noop.pipe(Instance carrier)`
`Instance` | `AugmentableFeatureVectorLogScale.pipe(Instance carrier)`
`Instance` | `Token2FeatureVector.pipe(Instance carrier)`
`Instance` | `TokenSequenceMatchDataAndTarget.pipe(Instance carrier)`
`Instance` | `SimpleTaggerSentence2TokenSequence.pipe(Instance carrier)` Takes an instance with data of type String or String[][] and creates an Instance of type TokenSequence.
`Instance` | `Filename2CharSequence.pipe(Instance carrier)`
`Instance` | `TargetStringToFeatures.pipe(Instance carrier)`
`Instance` | `TokenSequenceRemoveStopwords.pipe(Instance carrier)`
`Instance` | `TokenSequence2FeatureSequence.pipe(Instance carrier)`
`Instance` | `CharSequence2TokenSequence.pipe(Instance carrier)`
`Instance` | `Target2FeatureSequence.pipe(Instance carrier)`
`Instance` | `StringList2FeatureSequence.pipe(Instance carrier)`
`Instance` | `SimpleTokenizer.pipe(Instance instance)`
`Instance` | `Classification2ConfidencePredictingFeatureVector.pipe(Instance carrier)`
`Instance` | `TokenSequenceParseFeatureString.pipe(Instance carrier)`
`Instance` | `PrintTokenSequenceFeatures.pipe(Instance carrier)`
`Instance` | `CharSequence2CharNGrams.pipe(Instance carrier)`
`Instance` | `Target2LabelSequence.pipe(Instance carrier)`
`Instance` | `FeatureVectorConjunctions.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` | `SelectiveSGML2TokenSequence.pipe(Instance carrier)`

Methods in cc.mallet.pipe that return types with arguments of type Instance
`java.util.Iterator<Instance>` | `FilterEmptyFeatureVectors.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>` | `TokenSequence2TokenInstances.newIteratorFrom(java.util.Iterator<Instance> source)`
`java.util.Iterator<Instance>` | `SerialPipes.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` | `TokenSequenceRemoveNonAlpha.pipe(Instance carrier)`
`Instance` | `SimpleTaggerSentence2StringTokenization.pipe(Instance carrier)` Takes an instance with data of type String or String[][] and creates an Instance of type StringTokenization.
`Instance` | `Input2CharSequence.pipe(Instance carrier)`
`Instance` | `SGML2TokenSequence.pipe(Instance carrier)`
`Instance` | `FeatureSequence2AugmentableFeatureVector.pipe(Instance carrier)`
`Instance` | `MakeAmpersandXMLFriendly.pipe(Instance carrier)`
`Instance` | `AugmentableFeatureVectorAddConjunctions.pipe(Instance carrier)`
`Instance` | `TokenSequenceLowercase.pipe(Instance carrier)`
`Instance` | `CharSequenceReplace.pipe(Instance carrier)`
`Instance` | `SourceLocation2TokenSequence.pipe(Instance carrier)`
`Instance` | `PrintInput.pipe(Instance carrier)`
`Instance` | `CharSequenceArray2TokenSequence.pipe(Instance carrier)`
`Instance` | `Pipe.pipe(Instance inst)` Really this should be 'protected', but isn't for historical reasons.
`Instance` | `Target2Label.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` | `Directory2FileIterator.pipe(Instance carrier)`
`Instance` | `TargetRememberLastLabel.pipe(Instance carrier)`
`Instance` | `CharSequenceLowercase.pipe(Instance carrier)`
`Instance` | `FeatureSequence2FeatureVector.pipe(Instance carrier)`
`Instance` | `CharSubsequence.pipe(Instance carrier)`
`Instance` | `TokenSequenceNGrams.pipe(Instance carrier)`
`Instance` | `CharSequenceRemoveUUEncodedBlocks.pipe(Instance carrier)`
`Instance` | `FeatureCountPipe.pipe(Instance instance)`
`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` | `CharSequenceRemoveHTML.pipe(Instance carrier)`
`Instance` | `SaveDataInSource.pipe(Instance carrier)`
`Instance` | `FeatureValueString2FeatureVector.pipe(Instance carrier)`
`Instance` | `InstanceListTrimFeaturesByCount.pipe(Instance carrier)`
`Instance` | `TokenSequence2FeatureSequenceWithBigrams.pipe(Instance carrier)`
`Instance` | `LineGroupString2TokenSequence.pipe(Instance carrier)`
`Instance` | `TokenSequence2FeatureVectorSequence.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` | `PrintInputAndTarget.pipe(Instance carrier)`
`Instance` | `SvmLight2FeatureVectorAndLabel.pipe(Instance carrier)`
`Instance` | `AddClassifierTokenPredictions.pipe(Instance carrier)` Add the token classifier's predictions as features to the instance.
`Instance` | `StringAddNewLineDelimiter.pipe(Instance carrier)`
`Instance` | `Noop.pipe(Instance carrier)`
`Instance` | `AugmentableFeatureVectorLogScale.pipe(Instance carrier)`
`Instance` | `Token2FeatureVector.pipe(Instance carrier)`
`Instance` | `TokenSequenceMatchDataAndTarget.pipe(Instance carrier)`
`Instance` | `SimpleTaggerSentence2TokenSequence.pipe(Instance carrier)` Takes an instance with data of type String or String[][] and creates an Instance of type TokenSequence.
`Instance` | `Filename2CharSequence.pipe(Instance carrier)`
`Instance` | `TargetStringToFeatures.pipe(Instance carrier)`
`Instance` | `TokenSequenceRemoveStopwords.pipe(Instance carrier)`
`Instance` | `TokenSequence2FeatureSequence.pipe(Instance carrier)`
`Instance` | `CharSequence2TokenSequence.pipe(Instance carrier)`
`Instance` | `Target2FeatureSequence.pipe(Instance carrier)`
`Instance` | `StringList2FeatureSequence.pipe(Instance carrier)`
`Instance` | `SimpleTokenizer.pipe(Instance instance)`
`Instance` | `Classification2ConfidencePredictingFeatureVector.pipe(Instance carrier)`
`Instance` | `TokenSequenceParseFeatureString.pipe(Instance carrier)`
`Instance` | `PrintTokenSequenceFeatures.pipe(Instance carrier)`
`Instance` | `CharSequence2CharNGrams.pipe(Instance carrier)`
`Instance` | `Target2LabelSequence.pipe(Instance carrier)`
`Instance` | `FeatureVectorConjunctions.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` | `SelectiveSGML2TokenSequence.pipe(Instance carrier)`
`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>` | `FilterEmptyFeatureVectors.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>` | `TokenSequence2TokenInstances.newIteratorFrom(java.util.Iterator<Instance> source)`
`java.util.Iterator<Instance>` | `SerialPipes.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` | `LineGroupIterator.next()`
`Instance` | `CsvIterator.next()`
`Instance` | `SegmentIterator.next()`
`Instance` | `ParenGroupIterator.next()`
`Instance` | `SelectiveFileLineIterator.next()`
`Instance` | `FileListIterator.next()`
`Instance` | `ArrayDataAndTargetIterator.next()`
`Instance` | `RandomTokenSequenceIterator.next()`
`Instance` | `StringArrayIterator.next()`
`Instance` | `RandomFeatureVectorIterator.next()`
`Instance` | `PatternMatchIterator.next()`
`Instance` | `FileIterator.next()`
`Instance` | `ConcatenatedInstanceIterator.next()`
`Instance` | `UnlabeledFileIterator.next()`
`Instance` | `LineIterator.next()`
`Instance` | `EmptyInstanceIterator.next()`
`Instance` | `FileUriIterator.next()`
`abstract Instance` | `PipeInputIterator.next()` Deprecated.
`Instance` | `SimpleFileLineIterator.next()`
`Instance` | `ArrayIterator.next()`
`Instance` | `PipeExtendedIterator.next()` Deprecated.

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 `Segment`s 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` | `RegexMatches.pipe(Instance carrier)`
`Instance` | `LexiconMembership.pipe(Instance carrier)`
`Instance` | `TokenTextCharNGrams.pipe(Instance carrier)`
`Instance` | `TokenTextCharPrefix.pipe(Instance carrier)`
`Instance` | `CountMatchesMatching.pipe(Instance carrier)`
`Instance` | `TrieLexiconMembership.pipe(Instance carrier)`
`Instance` | `TokenFirstPosition.pipe(Instance instance)`
`Instance` | `FeaturesInWindow.pipe(Instance carrier)`
`Instance` | `TokenText.pipe(Instance carrier)`
`Instance` | `TokenTextCharSuffix.pipe(Instance carrier)`
`Instance` | `Target2BIOFormat.pipe(Instance carrier)`
`Instance` | `TokenTextNGrams.pipe(Instance carrier)`
`Instance` | `OffsetFeatureConjunction.pipe(Instance carrier)`
`Instance` | `CountMatches.pipe(Instance carrier)`
`Instance` | `SequencePrintingPipe.pipe(Instance carrier)`
`Instance` | `FeaturesOfFirstMention.pipe(Instance carrier)`
`Instance` | `OffsetPropertyConjunctions.pipe(Instance carrier)`
`Instance` | `OffsetConjunctions.pipe(Instance carrier)`
`Instance` | `CountMatchesAlignedWithOffsets.pipe(Instance carrier)`

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

Methods in cc.mallet.share.upenn.ner with parameters of type Instance
`Instance` | `ListMember.pipe(Instance carrier)`
`Instance` | `LengthBins.pipe(Instance carrier)`
`Instance` | `LongRegexMatches.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` | `MultiInstanceList.get(int index)`
`Instance` | `PagedInstanceList.get(int index)` Returns the `Instance` at the specified index.
`Instance` | `SingleInstanceIterator.next()`
`abstract Instance` | `ChainedInstanceIterator.next()` Deprecated.
`Instance` | `InstanceList.remove(int index)`
`Instance` | `MultiInstanceList.remove(int index)`
`Instance` | `InstanceList.set(int index, Instance instance)`
`Instance` | `MultiInstanceList.set(int index, Instance instance)`
`Instance` | `PagedInstanceList.set(int index, Instance instance)` Replaces the `Instance` at position `index` with a new one.
`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` | `InstanceList.add(Instance instance)` Appends the instance to this list without passing the instance through the InstanceList's pipe.
`boolean` | `MultiInstanceList.add(Instance instance)`
`boolean` | `PagedInstanceList.add(Instance instance)` Appends the instance to this list.
`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.
`boolean` | `MultiInstanceList.add(Instance instance, double instanceWeight)`
`void` | `InstanceList.add(int index, Instance element)`
`void` | `MultiInstanceList.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` | `InstanceList.remove(Instance instance)`
`boolean` | `MultiInstanceList.remove(Instance instance)`
`Instance` | `InstanceList.set(int index, Instance instance)`
`Instance` | `MultiInstanceList.set(int index, Instance instance)`
`Instance` | `PagedInstanceList.set(int index, Instance instance)` Replaces the `Instance` at position `index` with a new one.
`void` | `InstanceList.setInstance(int index, Instance instance)` Replaces the `Instance` at position `index` with a new one.
`void` | `MultiInstanceList.setInstance(int index, Instance instance)`
`void` | `InstanceList.setInstanceWeight(Instance instance, double weight)`
`void` | `MultiInstanceList.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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