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## Uses of Class
cc.mallet.pipe.Pipe

Packages that use Pipe
cc.mallet.classify | Classes for training and classifying instances.
cc.mallet.cluster | Unsupervised clustering of `Instance` objects within an `InstanceList`.
cc.mallet.cluster.tui |
cc.mallet.extract | Unimplemented.
cc.mallet.extract.pipe |
cc.mallet.fst | Transducers, including Conditional Random Fields (CRFs).
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.ner |
cc.mallet.share.weili.ner.enron |
cc.mallet.types | Fundamental MALLET types, including FeatureVector, Instance, Label etc.

Uses of Pipe in cc.mallet.classify

Fields in cc.mallet.classify declared as Pipe
`protected Pipe` | `Classifier.instancePipe`

Methods in cc.mallet.classify that return Pipe
`Pipe` | `Classifier.getInstancePipe()`

Methods in cc.mallet.classify with parameters of type Pipe
`static int` | `MaxEnt.getNumParameters(Pipe instancePipe)`

Constructors in cc.mallet.classify with parameters of type Pipe
`AdaBoost(Pipe instancePipe, Classifier[] weakClassifiers, double[] alphas)`
`AdaBoostM2(Pipe instancePipe, Classifier[] weakClassifiers, double[] alphas)`
`BaggingClassifier(Pipe instancePipe, Classifier[] baggedClassifiers)`
`BalancedWinnow(Pipe dataPipe, double[][] weights)` Passes along data pipe and weights from `BalancedWinnowTrainer`
`C45(Pipe instancePipe, C45.Node root)`
`Classifier(Pipe instancePipe)`
`ConfidencePredictingClassifierTrainer(ClassifierTrainer underlyingClassifierTrainer, InstanceList validationSet, Pipe confidencePredictingPipe)`
`DecisionTree(Pipe instancePipe, DecisionTree.Node root)`
`MaxEnt(Pipe dataPipe, double[] parameters)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, FeatureSelection[] perClassFeatureSelection)`
`MCMaxEnt(Pipe dataPipe, double[] parameters)`
`MCMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`MCMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`MCMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, FeatureSelection[] perClassFeatureSelection)`
`NaiveBayes(Pipe instancePipe, Multinomial.Logged prior, Multinomial.Logged[] classIndex2FeatureProb)` Construct a NaiveBayes classifier from a pipe, prior estimates for each Classification, and feature estimates of each Classification.
`NaiveBayes(Pipe dataPipe, Multinomial prior, Multinomial[] classIndex2FeatureProb)` Construct a NaiveBayes classifier from a pipe, prior estimates for each Classification, and feature estimates of each Classification.
`NaiveBayesTrainer(Pipe instancePipe)`
`RankMaxEnt(Pipe dataPipe, double[] parameters)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, FeatureSelection[] perClassFeatureSelection)`
`Winnow(Pipe dataPipe, double[][] newWeights, double theta, int idim, int jdim)` Passes along data pipe and weights from `WinnowTrainer`

Uses of Pipe in cc.mallet.cluster

Methods in cc.mallet.cluster that return Pipe
`Pipe` | `Clusterer.getPipe()`

Constructors in cc.mallet.cluster with parameters of type Pipe
`Clusterer(Pipe instancePipe)` Creates a new `Clusterer` instance.
`GreedyAgglomerative(Pipe instancePipe, NeighborEvaluator evaluator, double stoppingThreshold)`
`GreedyAgglomerativeByDensity(Pipe instancePipe, NeighborEvaluator evaluator, double stoppingThreshold, boolean doPostConvergenceMerges, java.util.Random random)`
`HillClimbingClusterer(Pipe instancePipe, NeighborEvaluator evaluator)`
`KBestClusterer(Pipe instancePipe)`
`KMeans(Pipe instancePipe, int numClusters, Metric metric)` Construct a KMeans object
`KMeans(Pipe instancePipe, int numClusters, Metric metric, int emptyAction)` Construct a KMeans object

Uses of Pipe in cc.mallet.cluster.tui

Subclasses of Pipe in cc.mallet.cluster.tui
`static class` | `Clusterings2Clusterer.ClusteringPipe`

Uses of Pipe in cc.mallet.extract

Methods in cc.mallet.extract that return Pipe
`Pipe` | `CRFExtractor.getFeaturePipe()`
`Pipe` | `Extractor.getFeaturePipe()` Returns the pipe used by this extractor for.
`Pipe` | `CRFExtractor.getTokenizationPipe()`
`Pipe` | `Extractor.getTokenizationPipe()` Returns the pipe used by this extractor to tokenize the input.

Methods in cc.mallet.extract with parameters of type Pipe
`void` | `CRFExtractor.setFeaturePipe(Pipe featurePipe)`
`void` | `CRFExtractor.setTokenizationPipe(Pipe tokenizationPipe)`
`void` | `Extractor.setTokenizationPipe(Pipe pipe)` Sets the pipe used by this extractor for tokenization.

Constructors in cc.mallet.extract with parameters of type Pipe
`CRFExtractor(CRF crf, Pipe tokpipe)`
`CRFExtractor(CRF crf, Pipe tokpipe, TokenizationFilter filter)`
`CRFExtractor(CRF crf, Pipe tokpipe, TokenizationFilter filter, java.lang.String backgroundTag)`
`TransducerExtractionConfidenceEstimator(TransducerConfidenceEstimator confidenceEstimator, java.lang.Object[] startTags, java.lang.Object[] continueTags, Pipe featurePipe)`

Uses of Pipe in cc.mallet.extract.pipe

Subclasses of Pipe in cc.mallet.extract.pipe
`class` | `TokenSequence2Tokenization` Heuristically converts a simple token sequence into a Tokenization that can be used with all the extract package goodies.

Uses of Pipe in cc.mallet.fst

Subclasses of Pipe in cc.mallet.fst
`static class` | `SimpleTagger.SimpleTaggerSentence2FeatureVectorSequence` Converts an external encoding of a sequence of elements with binary features to a `FeatureVectorSequence`.

Fields in cc.mallet.fst declared as Pipe
`protected Pipe` | `Transducer.inputPipe` A pipe that should produce a Sequence in the "data" slot, (and possibly one in the "target" slot also
`protected Pipe` | `Transducer.outputPipe` A pipe that should expect the Transducer's output sequence in the "target" slot, and should produce something printable in the "source" slot that indicates the results of transduction.

Methods in cc.mallet.fst that return Pipe
`Pipe` | `Transducer.getInputPipe()`
`Pipe` | `Transducer.getOutputPipe()`

Constructors in cc.mallet.fst with parameters of type Pipe
`CRF(Pipe inputPipe, Pipe outputPipe)`
`HMM(Pipe inputPipe, Pipe outputPipe)`
`MEMM(Pipe inputPipe, Pipe outputPipe)`
`Transducer(Pipe inputPipe, Pipe outputPipe)`

Uses of Pipe in cc.mallet.fst.tests

Subclasses of Pipe in cc.mallet.fst.tests
`class` | `TestCRF.TestCRF2String`
`static class` | `TestCRF.TestCRFTokenSequenceRemoveSpaces`
`class` | `TestMEMM.TestMEMM2String`
`static class` | `TestMEMM.TestMEMMTokenSequenceRemoveSpaces`

Methods in cc.mallet.fst.tests that return Pipe
`static Pipe` | `TestMEMM.makeSpacePredictionPipe()`

Uses of Pipe in cc.mallet.grmm.learning

Subclasses of Pipe in cc.mallet.grmm.learning
`class` | `GenericAcrfData2TokenSequence` Generic pipe that takes a linegroup of the form:

Methods in cc.mallet.grmm.learning that return Pipe
`Pipe` | `ACRF.getInputPipe()`

Methods in cc.mallet.grmm.learning with parameters of type Pipe
`static ACRF` | `ACRF.makeFactorial(Pipe p, int numLevels)`

Constructors in cc.mallet.grmm.learning with parameters of type Pipe
`ACRF(Pipe inputPipe, ACRF.Template[] tmpls)` Create a ACRF for a 1-d sequence.

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

Fields in cc.mallet.grmm.learning.extract declared as Pipe
`protected Pipe` | `ACRFExtractorTrainer.featurePipe`
`protected Pipe` | `ACRFExtractorTrainer.tokPipe`

Methods in cc.mallet.grmm.learning.extract that return Pipe
`Pipe` | `ACRFExtractor.getFeaturePipe()`
`Pipe` | `ACRFExtractor.getTokenizationPipe()`

Methods in cc.mallet.grmm.learning.extract with parameters of type Pipe
`ACRFExtractorTrainer` | `ACRFExtractorTrainer.setPipes(Pipe tokPipe, Pipe featurePipe)`
`void` | `ACRFExtractor.setTokenizationPipe(Pipe pipe)`

Constructors in cc.mallet.grmm.learning.extract with parameters of type Pipe
`ACRFExtractor(ACRF acrf, Pipe tokPipe, Pipe featurePipe)`

Uses of Pipe in cc.mallet.grmm.util

Subclasses of Pipe in cc.mallet.grmm.util
`class` | `LabelsSequence2Assignment` $Id: LabelsSequence2Assignment.java,v 1.1 2007/10/22 21:37:58 mccallum Exp $
`class` | `RememberTokenizationPipe` Created: Mar 17, 2005
`class` | `SliceLabelsSequence` * Created: Fri Jan 02 23:27:04 2004

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

Uses of Pipe in cc.mallet.pipe

Subclasses of Pipe in cc.mallet.pipe
`class` | `AddClassifierTokenPredictions` This pipe uses a Classifier to label each token (i.e., using 0-th order Markov assumption), then adds the predictions as features to each token.
`class` | `Array2FeatureVector` Converts a Java array of numerical types to a FeatureVector, where the Alphabet is the data array index wrapped in an Integer object.
`class` | `AugmentableFeatureVectorAddConjunctions` Add specified conjunctions to each instance.
`class` | `AugmentableFeatureVectorLogScale` Given an AugmentableFeatureVector, set those values greater than or equal to 1 to log(value)+1.
`class` | `BranchingPipe` Deprecated.
`class` | `CharSequence2CharNGrams` Transform a character sequence into a token sequence of character N grams.
`class` | `CharSequence2TokenSequence` Pipe that tokenizes a character sequence.
`class` | `CharSequenceArray2TokenSequence` Transform an array of character Sequences into a token sequence.
`class` | `CharSequenceLowercase` Replace the data string with a lowercased version.
`class` | `CharSequenceRemoveHTML` This pipe removes HTML from a CharSequence.
`class` | `CharSequenceRemoveUUEncodedBlocks`
`class` | `CharSequenceReplace` Given a string, repeatedly look for matches of the regex, and replace the entire match with the given replacement string.
`class` | `CharSubsequence` Given a string, return only the portion of the string inside a regex parenthesized group.
`class` | `Classification2ConfidencePredictingFeatureVector` Pipe features from underlying classifier to the confidence prediction instance list
`class` | `Csv2Array` Converts a string of comma separated values to an array.
`class` | `Csv2FeatureVector` Converts a string of the form `feature_1:val_1 feature_2:val_2 ...`
`class` | `Directory2FileIterator` Convert a File object representing a directory into a FileIterator which iterates over files in the directory matching a pattern and which extracts a label from each file path to become the target field of the instance.
`class` | `FeatureCountPipe` Pruning low-count features can be a good way to save memory and computation.
`class` | `FeatureSequence2AugmentableFeatureVector` Convert the data field from a feature sequence to an augmentable feature vector.
`class` | `FeatureSequence2FeatureVector` Convert the data field from a feature sequence to a feature vector.
`class` | `FeatureSequenceConvolution`
`class` | `FeatureValueString2FeatureVector`
`class` | `FeatureVectorConjunctions` Include in the FeatureVector conjunctions of all its features.
`class` | `FeatureVectorSequence2FeatureVectors` Given instances with a FeatureVectorSequence in the data field, break up the sequence into the individual FeatureVectors, producing one FeatureVector per Instance.
`class` | `Filename2CharSequence` Given a filename contained in a string, read in contents of file into a CharSequence.
`class` | `FilterEmptyFeatureVectors`
`class` | `Input2CharSequence` Pipe that can read from various kinds of text sources (either URI, File, or Reader) into a CharSequence
`class` | `InstanceListTrimFeaturesByCount` Unimplemented.
`class` | `LineGroupString2TokenSequence`
`class` | `MakeAmpersandXMLFriendly` convert & to &amp in tokens of a token sequence
`class` | `Noop` A pipe that does nothing to the instance fields but which has side effects on the dictionary.
`class` | `PrintInput` Print the data field of each instance.
`class` | `PrintInputAndTarget` Print the data and target fields of each instance.
`class` | `PrintTokenSequenceFeatures` Print properties of the token sequence in the data field and the corresponding value of any token in a token sequence or feature in a featur sequence in the target field.
`class` | `SaveDataInSource` Set the source field of each instance to its data field.
`class` | `SelectiveSGML2TokenSequence` Similar to `SGML2TokenSequence`, except that only the tags listed in `allowedTags` are converted to `Label`s.
`class` | `SerialPipes` Convert an instance through a sequence of pipes.
`class` | `SGML2TokenSequence` Converts a string containing simple SGML tags into a dta TokenSequence of words, paired with a target TokenSequence containing the SGML tags in effect for each word.
`class` | `SimpleTaggerSentence2StringTokenization` This extends `SimpleTaggerSentence2TokenSequence` to use {Slink StringTokenizations} for use with the extract package.
`class` | `SimpleTaggerSentence2TokenSequence` Converts an external encoding of a sequence of elements with binary features to a `TokenSequence`.
`class` | `SimpleTokenizer` A simple unicode tokenizer that accepts sequences of letters as tokens.
`class` | `SourceLocation2TokenSequence` Read from File or BufferedRead in the data field and produce a TokenSequence.
`class` | `StringAddNewLineDelimiter` Pipe that can adds special text between lines to explicitly represent line breaks.
`class` | `StringList2FeatureSequence` Convert a list of strings into a feature sequence
`class` | `SvmLight2FeatureVectorAndLabel` This Pipe converts a line in SVMLight format to a Mallet instance with FeatureVector data and Label target.
`class` | `Target2FeatureSequence` Convert a token sequence in the target field into a feature sequence in the target field.
`class` | `Target2Label` Convert object in the target field into a label in the target field.
`class` | `Target2LabelSequence` convert a token sequence in the target field into a label sequence in the target field.
`class` | `TargetRememberLastLabel` For each position in the target, remember the last non-background label.
`class` | `TargetStringToFeatures`
`class` | `Token2FeatureVector` convert the property list on a token into a feature vector
`class` | `TokenSequence2FeatureSequence` Convert the token sequence in the data field each instance to a feature sequence.
`class` | `TokenSequence2FeatureSequenceWithBigrams` Convert the token sequence in the data field of each instance to a feature sequence that preserves bigram information.
`class` | `TokenSequence2FeatureVectorSequence` Convert the token sequence in the data field of each instance to a feature vector sequence.
`class` | `TokenSequence2TokenInstances`
`class` | `TokenSequenceLowercase` Convert the text in each token in the token sequence in the data field to lower case.
`class` | `TokenSequenceMatchDataAndTarget` Run a regular expression over the text of each token; replace the text with the substring matching one regex group; create a target TokenSequence from the text matching another regex group.
`class` | `TokenSequenceNGrams` Convert the token sequence in the data field to a token sequence of ngrams.
`class` | `TokenSequenceParseFeatureString` Convert the string in each field `Token.text` to a list of Strings (space delimited).
`class` | `TokenSequenceRemoveNonAlpha` Remove tokens that contain non-alphabetic characters.
`class` | `TokenSequenceRemoveStopwords` Remove tokens from the token sequence in the data field whose text is in the stopword list.

Methods in cc.mallet.pipe that return Pipe
`static Pipe` | `PipeUtils.concatenatePipes(Pipe p1, Pipe p2)`
`Pipe` | `SerialPipes.getPipe(int index)`

Methods in cc.mallet.pipe that return types with arguments of type Pipe
`java.util.ArrayList<Pipe>` | `SerialPipes.pipes()` Allows access to the underlying collection of Pipes.

Methods in cc.mallet.pipe with parameters of type Pipe
`static Pipe` | `PipeUtils.concatenatePipes(Pipe p1, Pipe p2)`
`abstract boolean` | `SerialPipes.Predicate.predicate(Pipe p)`
`static void` | `AddClassifierTokenPredictions.setInProduction(Pipe p, boolean value)`

Constructors in cc.mallet.pipe with parameters of type Pipe
`BranchingPipe(Pipe[] pipes)` Deprecated.
`SerialPipes(Pipe[] pipes)`

Constructor parameters in cc.mallet.pipe with type arguments of type Pipe
`BranchingPipe(java.util.Collection<Pipe> pipeList)` Deprecated.
`SerialPipes(java.util.Collection<Pipe> pipeList)`

Uses of Pipe in cc.mallet.pipe.iterator

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

Uses of Pipe in cc.mallet.pipe.tests

Subclasses of Pipe in cc.mallet.pipe.tests
`static class` | `TestInstancePipe.Array2ArrayIterator`
`static class` | `TestSGML2TokenSequence.Array2ArrayIterator`

Methods in cc.mallet.pipe.tests that return Pipe
`Pipe` | `TestInstancePipe.createPipe()`

Uses of Pipe in cc.mallet.pipe.tsf

Subclasses of Pipe in cc.mallet.pipe.tsf
`class` | `CountMatches`
`class` | `CountMatchesAlignedWithOffsets`
`class` | `CountMatchesMatching`
`class` | `FeaturesInWindow`
`class` | `FeaturesOfFirstMention`
`class` | `LexiconMembership`
`class` | `OffsetConjunctions`
`class` | `OffsetFeatureConjunction`
`class` | `OffsetPropertyConjunctions`
`class` | `RegexMatches`
`class` | `SequencePrintingPipe` Created: Jul 6, 2005
`class` | `Target2BIOFormat` Creates a `LabelSequence` out of a `TokenSequence` that is the target of an `Instance`.
`class` | `TokenFirstPosition`
`class` | `TokenText`
`class` | `TokenTextCharNGrams`
`class` | `TokenTextCharPrefix`
`class` | `TokenTextCharSuffix`
`class` | `TokenTextNGrams`
`class` | `TrieLexiconMembership`

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

Subclasses of Pipe in cc.mallet.share.casutton.ner
`class` | `ConllNer2003Sentence2TokenSequence` Reads a data file in CoNLL 2003 format, and makes some simple transformations.

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

Subclasses of Pipe in cc.mallet.share.mccallum.ner
`class` | `TokenSequenceDocHeader`

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

Subclasses of Pipe in cc.mallet.share.upenn.ner
`class` | `FeatureWindow` Adds all features of tokens in the window to the center token.
`class` | `LengthBins` A feature approximating string length.
`class` | `ListMember` Checks membership in a lexicon in a text file.
`class` | `LongRegexMatches` Matches a regular expression which spans several tokens.
`class` | `NEPipes`

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

Subclasses of Pipe in cc.mallet.share.weili.ner.enron
`class` | `EnronMessage2TokenSequence`

Uses of Pipe in cc.mallet.types

Methods in cc.mallet.types that return Pipe
`Pipe` | `InstanceList.getPipe()` Returns the pipe through which each added `Instance` is passed, which may be `null`.

Methods in cc.mallet.types with parameters of type Pipe
`void` | `InstanceList.setPipe(Pipe p)` Change the default Pipe associated with InstanceList.

Constructors in cc.mallet.types with parameters of type Pipe
`InstanceList(Pipe pipe)` Construct an InstanceList with initial capacity of 10, with given default pipe.
`InstanceList(Pipe pipe, int capacity)` Construct an InstanceList having given capacity, with given default pipe.
`PagedInstanceList(Pipe pipe, int numPages, int instancesPerPage)`
`PagedInstanceList(Pipe pipe, int numPages, int instancesPerPage, java.io.File swapDir)` Creates a PagedInstanceList where "instancesPerPage" instances are swapped to disk in directory "swapDir" if the amount of free system memory drops below "minFreeMemory" bytes

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