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## Uses of Interface
cc.mallet.types.Sequence

Packages that use Sequence
cc.mallet.extract | Unimplemented.
cc.mallet.fst | Transducers, including Conditional Random Fields (CRFs).
cc.mallet.fst.confidence |
cc.mallet.grmm.learning |
cc.mallet.pipe.iterator | Classes that generate instances from different kinds of input or data structures.
cc.mallet.types | Fundamental MALLET types, including FeatureVector, Instance, Label etc.
cc.mallet.util | Miscellaneous utilities including command line processing, math functions, lexing, logging.

Uses of Sequence in cc.mallet.extract

Subinterfaces of Sequence in cc.mallet.extract
`interface` | `Tokenization`

Classes in cc.mallet.extract that implement Sequence
`class` | `LabeledSpans` Created: Oct 31, 2004
`class` | `StringTokenization`

Methods in cc.mallet.extract that return Sequence
`Sequence` | `DocumentExtraction.getPredictedLabels()`
`Sequence` | `CRFExtractor.pipeInput(java.lang.Object input)`

Methods in cc.mallet.extract with parameters of type Sequence
`LabeledSpans` | `BIOTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)`
`LabeledSpans` | `HierarchicalTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)`
`LabeledSpans` | `TokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)` Converts a the sequence of labels into a set of labeled spans.
`LabeledSpans` | `ConfidenceTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)`
`LabeledSpans` | `DefaultTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)`

Constructors in cc.mallet.extract with parameters of type Sequence
`DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background)`
`DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background)`
`DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background, TokenizationFilter filter)`
`DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background, TokenizationFilter filter)`
`DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, java.lang.String background)`
`Extraction(Extractor extractor, LabelAlphabet dict, java.lang.String name, Tokenization input, Sequence output, java.lang.String background)` Creates an extration given a sequence output by some kind of per-sequece labeler, like an HMM or a CRF.

Uses of Sequence in cc.mallet.fst

Methods in cc.mallet.fst that return Sequence
`static Sequence[]` | `SimpleTagger.apply(Transducer model, Sequence input, int k)` Apply a transducer to an input sequence to produce the k highest-scoring output sequences.
`Sequence<java.lang.Object>` | `MaxLattice.bestOutputSequence()`
`Sequence<java.lang.Object>` | `MaxLatticeDefault.bestOutputSequence()`
`Sequence<Transducer.State>` | `MaxLattice.bestStateSequence()`
`Sequence<Transducer.State>` | `MaxLatticeDefault.bestStateSequence()`
`Sequence` | `Segment.getInput()`
`Sequence` | `MaxLatticeDefault.getInput()`
`Sequence` | `Segment.getPredicted()`
`Sequence` | `MaxLatticeDefault.getProvidedOutput()`
`Sequence` | `Segment.getSegmentInputSequence()`
`Sequence` | `Segment.getTruth()`
`Sequence[]` | `CRF.predict(InstanceList testing)` Deprecated.
`Sequence` | `Transducer.transduce(Sequence input)` Converts the given sequence into another sequence according to this transducer.

Methods in cc.mallet.fst that return types with arguments of type Sequence
`java.util.List<Sequence<java.lang.Object>>` | `MaxLattice.bestOutputSequences(int n)`
`java.util.List<Sequence<java.lang.Object>>` | `MaxLatticeDefault.bestOutputSequences(int n)`
`java.util.List<Sequence<Transducer.State>>` | `MaxLattice.bestStateSequences(int n)`
`java.util.List<Sequence<Transducer.State>>` | `MaxLatticeDefault.bestStateSequences(int n)`

Methods in cc.mallet.fst with parameters of type Sequence
`static Sequence[]` | `SimpleTagger.apply(Transducer model, Sequence input, int k)` Apply a transducer to an input sequence to produce the k highest-scoring output sequences.
`double` | `MaxLattice.elementwiseAccuracy(Sequence referenceOutput)`
`double` | `MaxLatticeDefault.elementwiseAccuracy(Sequence referenceOutput)`
`MaxLattice` | `MaxLatticeFactory.newMaxLattice(Transducer trans, Sequence inputSequence)`
`MaxLattice` | `MaxLatticeDefault.Factory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)`
`MaxLattice` | `MaxLatticeDefault.Factory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)`
`abstract MaxLattice` | `MaxLatticeFactory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)`
`abstract MaxLattice` | `MaxLatticeFactory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`abstract SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)` Returns a SumLattice object to run forward-backward.
`abstract SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)` Returns a SumLattice object to run forward-backward.
`SumLattice` | `SumLatticeDefault.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeDefault.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeBeam.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeBeam.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeScaling.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeScaling.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)`
`SumLattice` | `SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Transducer.Incrementor incrementor)`
`int` | `MultiSegmentationEvaluator.numIncorrectSegments(Sequence trueOutput, Sequence predOutput)` Returns the number of incorrect segments in `predOutput`
`int` | `MultiSegmentationEvaluator.numIncorrectSegments(Sequence trueOutput, Sequence predOutput)` Returns the number of incorrect segments in `predOutput`
`void` | `Segment.setPredicted(Sequence predicted)`
`double` | `MaxLatticeDefault.tokenAccuracy(Sequence referenceOutput, java.io.PrintWriter out)`
`Sequence` | `Transducer.transduce(Sequence input)` Converts the given sequence into another sequence according to this transducer.
`Transducer.TransitionIterator` | `FeatureTransducer.State.transitionIterator(Sequence inputSequence, int inputPosition)`
`Transducer.TransitionIterator` | `Transducer.State.transitionIterator(Sequence input, int inputPosition)`
`Transducer.TransitionIterator` | `FeatureTransducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)`
`Transducer.TransitionIterator` | `FeatureTransducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)`
`Transducer.TransitionIterator` | `CRF.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)`
`Transducer.TransitionIterator` | `CRF.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)`
`Transducer.TransitionIterator` | `MEMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)`
`Transducer.TransitionIterator` | `MEMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)`
`Transducer.TransitionIterator` | `HMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)`
`Transducer.TransitionIterator` | `HMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)`
`abstract Transducer.TransitionIterator` | `Transducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)`
`abstract Transducer.TransitionIterator` | `Transducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)`

Method parameters in cc.mallet.fst with type arguments of type Sequence
`void` | `MultiSegmentationEvaluator.batchTest(InstanceList data, java.util.List<Sequence> predictedSequences, java.lang.String description, java.io.PrintStream viterbiOutputStream)` Tests segmentation using an ArrayList of predicted Sequences instead of a `Transducer`.

Constructors in cc.mallet.fst with parameters of type Sequence
`MaxLatticeDefault(Transducer t, Sequence inputSequence)`
`MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence)`
`MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence)`
`MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence, int maxCaches)` Initiate Viterbi decoding of the inputSequence, contrained to match non-null parts of the outputSequence.
`MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence, int maxCaches)` Initiate Viterbi decoding of the inputSequence, contrained to match non-null parts of the outputSequence.
`Segment(Sequence input, Sequence pred, Sequence truth, int start, int end, java.lang.Object startTag, java.lang.Object inTag)` Initializes the segment.
`Segment(Sequence input, Sequence pred, Sequence truth, int start, int end, java.lang.Object startTag, java.lang.Object inTag)` Initializes the segment.
`Segment(Sequence input, Sequence pred, Sequence truth, int start, int end, java.lang.Object startTag, java.lang.Object inTag)` Initializes the segment.
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)` Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.
`SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)` Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.
`SumLatticeConstrained(Transducer t, Sequence input, Sequence output, Segment requiredSegment, Sequence constrainedSequence)`
`SumLatticeConstrained(Transducer t, Sequence input, Sequence output, Segment requiredSegment, Sequence constrainedSequence)`
`SumLatticeConstrained(Transducer t, Sequence input, Sequence output, Segment requiredSegment, Sequence constrainedSequence)`
`SumLatticeConstrained(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)` Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.
`SumLatticeConstrained(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)` Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.
`SumLatticeDefault(Transducer trans, Sequence input)`
`SumLatticeDefault(Transducer trans, Sequence input, boolean saveXis)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)`
`SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)`
`SumLatticeDefault(Transducer trans, Sequence input, Transducer.Incrementor incrementor)`
`SumLatticeScaling(Transducer trans, Sequence input)`
`SumLatticeScaling(Transducer trans, Sequence input, boolean saveXis)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)`
`SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)`
`SumLatticeScaling(Transducer trans, Sequence input, Transducer.Incrementor incrementor)`

Uses of Sequence in cc.mallet.fst.confidence

Constructors in cc.mallet.fst.confidence with parameters of type Sequence
`ConfidenceEvaluator.EntityConfidence(double conf, boolean corr, Sequence input, int start, int end)`
`InstanceWithConfidence(Instance inst, double c, Sequence predicted)`

Uses of Sequence in cc.mallet.grmm.learning

Methods in cc.mallet.grmm.learning with parameters of type Sequence
`void` | `MultiSegmentationEvaluatorACRF.TestResults.incrementCounts(Sequence trueOutput, Sequence predOutput)`
`void` | `MultiSegmentationEvaluatorACRF.TestResults.incrementCounts(Sequence trueOutput, Sequence predOutput)`

Uses of Sequence in cc.mallet.pipe.iterator

Constructors in cc.mallet.pipe.iterator with parameters of type Sequence
`SegmentIterator(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags, Sequence prediction)` Iterate over segments in one instance.
`SegmentIterator(Sequence input, Sequence predicted, Sequence truth, java.lang.Object[] startTags, java.lang.Object[] inTags)` Iterate over segments in one labeled sequence
`SegmentIterator(Sequence input, Sequence predicted, Sequence truth, java.lang.Object[] startTags, java.lang.Object[] inTags)` Iterate over segments in one labeled sequence
`SegmentIterator(Sequence input, Sequence predicted, Sequence truth, java.lang.Object[] startTags, java.lang.Object[] inTags)` Iterate over segments in one labeled sequence

Uses of Sequence in cc.mallet.types

Classes in cc.mallet.types that implement Sequence
`class` | `ArrayListSequence<E>`
`class` | `ArraySequence<E>`
`class` | `FeatureSequence` An implementation of `Sequence` that ensures that every Object in the sequence has the same class.
`class` | `FeatureSequenceWithBigrams` A FeatureSequence with a parallel record of bigrams, kept in a separate dictionary
`class` | `FeatureVectorSequence`
`class` | `LabelSequence`
`class` | `LabelsSequence` A simple `Sequence` implementation where all of the elements must be Labels.
`class` | `StringEditFeatureVectorSequence`
`class` | `TokenSequence` A representation of a piece of text, usually a single word, to which we can attach properties.

Fields in cc.mallet.types declared as Sequence
`protected Sequence<I>` | `SequencePair.input`
`protected Sequence<O>` | `SequencePair.output`

Methods in cc.mallet.types that return Sequence
`Sequence<I>` | `SequencePair.input()`
`Sequence<O>` | `SequencePair.output()`

Constructors in cc.mallet.types with parameters of type Sequence
`ArraySequence(Sequence<E> s, boolean copy)`
`SequencePair(Sequence<I> input, Sequence<O> output)`
`SequencePair(Sequence<I> input, Sequence<O> output)`
`SequencePairAlignment(Sequence<I> input, Sequence<O> output, double weight)`
`SequencePairAlignment(Sequence<I> input, Sequence<O> output, double weight)`

Uses of Sequence in cc.mallet.util

Methods in cc.mallet.util with parameters of type Sequence
`static double` | `Sequences.elementwiseAccuracy(Sequence truth, Sequence predicted)`
`static double` | `Sequences.elementwiseAccuracy(Sequence truth, Sequence predicted)`

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