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abs(double) - Static method in class edu.cmu.minorthird.util.MathUtil: Absolute value function.
AbstractAnnotator - Class in edu.cmu.minorthird.text: Generic implementation of an annotator.
AbstractAnnotator() - Constructor for class edu.cmu.minorthird.text.AbstractAnnotator
AbstractBatchAnnotatorLearner - Class in edu.cmu.minorthird.text.learn: Learn an annotation model using a sequence dataset and some sort of batch learner.
AbstractBatchAnnotatorLearner() - Constructor for class edu.cmu.minorthird.text.learn.AbstractBatchAnnotatorLearner
AbstractBatchAnnotatorLearner(SpanFeatureExtractor, Extraction2TaggingReduction) - Constructor for class edu.cmu.minorthird.text.learn.AbstractBatchAnnotatorLearner
AbstractInstance - Class in edu.cmu.minorthird.classify: Common code for all instance implementations
AbstractInstance() - Constructor for class edu.cmu.minorthird.classify.AbstractInstance
AbstractInstanceTransform - Class in edu.cmu.minorthird.classify.transform
AbstractInstanceTransform() - Constructor for class edu.cmu.minorthird.classify.transform.AbstractInstanceTransform
AbstractLooper<T> - Class in edu.cmu.minorthird.util
AbstractLooper(Iterator<T>) - Constructor for class edu.cmu.minorthird.util.AbstractLooper
AbstractLooper(Collection<T>) - Constructor for class edu.cmu.minorthird.util.AbstractLooper
AbstractSpanFinder - Class in edu.cmu.minorthird.text: Abstract implementation of a SpanFinder.
AbstractSpanFinder() - Constructor for class edu.cmu.minorthird.text.AbstractSpanFinder
AbstractTextBase - Class in edu.cmu.minorthird.text
AbstractTextBase(Tokenizer) - Constructor for class edu.cmu.minorthird.text.AbstractTextBase
acc_sf1() - Method in class edu.cmu.minorthird.text.learn.experiments.ExtractionEvaluation
acc_sp() - Method in class edu.cmu.minorthird.text.learn.experiments.ExtractionEvaluation
acc_sr() - Method in class edu.cmu.minorthird.text.learn.experiments.ExtractionEvaluation
acc_tf1() - Method in class edu.cmu.minorthird.text.learn.experiments.ExtractionEvaluation
acc_tp() - Method in class edu.cmu.minorthird.text.learn.experiments.ExtractionEvaluation
acc_tr() - Method in class edu.cmu.minorthird.text.learn.experiments.ExtractionEvaluation
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.text.gui.OnlineClassifierDocumentEditor.MoveOnlineDocumentCursor
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.text.gui.OnlineLearnerEditor.EditTypeAction
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.text.gui.TextBaseEditor.EditTypeAction
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.text.gui.TextBaseViewer.HighlightAction
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.text.gui.ViewerTracker.MoveDocumentCursor
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.text.gui.ViewerTracker.SaveLabelsAction
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.ui.FileChooserViewer
actionPerformed(ActionEvent) - Method in class edu.cmu.minorthird.util.gui.ViewerControls
actual(String) - Method in class edu.cmu.minorthird.text.SpanDifference.Invoker
actualType - Variable in class edu.cmu.minorthird.text.SpanDifference.Invoker
AdaBoost - Class in edu.cmu.minorthird.classify.algorithms.trees: Generalized version of AdaBoost, as described in Robert E.
AdaBoost() - Constructor for class edu.cmu.minorthird.classify.algorithms.trees.AdaBoost
AdaBoost(BatchClassifierLearner, int) - Constructor for class edu.cmu.minorthird.classify.algorithms.trees.AdaBoost
AdaBoost.L - Class in edu.cmu.minorthird.classify.algorithms.trees: AdaBoost.L is a logistic-regression version of AdaBoost.
AdaBoost.L() - Constructor for class edu.cmu.minorthird.classify.algorithms.trees.AdaBoost.L
AdaBoost.L(BatchClassifierLearner, int) - Constructor for class edu.cmu.minorthird.classify.algorithms.trees.AdaBoost.L
add(Example) - Method in class edu.cmu.minorthird.classify.BasicDataset: Add an example to the dataset.
add(Example, boolean) - Method in class edu.cmu.minorthird.classify.BasicDataset: Add an Example to the dataset.
add(String, double) - Method in class edu.cmu.minorthird.classify.ClassLabel: Add a label with the given weight to this ClassLabel.
add(Example) - Method in interface edu.cmu.minorthird.classify.Dataset: Add a new example to the dataset.
add(Example, boolean) - Method in interface edu.cmu.minorthird.classify.Dataset: Add a new example to the dataset.
add(String, Evaluation) - Method in class edu.cmu.minorthird.classify.experiments.EvaluationGroup: Add an evaluation to the group
add(Example) - Method in class edu.cmu.minorthird.classify.multi.MultiDataset
add(Example, boolean) - Method in class edu.cmu.minorthird.classify.multi.MultiDataset
add(Example) - Method in class edu.cmu.minorthird.classify.semisupervised.SemiSupervisedDataset: Add an example to the dataset.
add(Example, boolean) - Method in class edu.cmu.minorthird.classify.semisupervised.SemiSupervisedDataset: Add an Example to the dataset.
add(Segmentation.Segment) - Method in class edu.cmu.minorthird.classify.sequential.Segmentation
add(Example) - Method in class edu.cmu.minorthird.classify.sequential.SegmentDataset: Add an example to the dataset.
add(Example, boolean) - Method in class edu.cmu.minorthird.classify.sequential.SegmentDataset: Add an Example to the dataset.
add(Example) - Method in class edu.cmu.minorthird.classify.sequential.SequenceDataset: Add a new example to the dataset.
add(Example, boolean) - Method in class edu.cmu.minorthird.classify.sequential.SequenceDataset: Add a new example to the dataset.
add(T, double) - Method in class edu.cmu.minorthird.classify.WeightedSet: Add a new object.
add() - Method in class edu.cmu.minorthird.text.gui.OnlineClassifierDocumentEditor.EditedSpan
add(double) - Method in class edu.cmu.minorthird.util.MathUtil.Accumulator: Add a new number to the accumulator.
addActionListener(ActionListener) - Method in class edu.cmu.minorthird.ui.FileChooserViewer
addAggregator(String, String) - Static method in class edu.cmu.minorthird.classify.relational.RealRelationalDataset: Add an aggregator, i.e., save the info.
addApplyButton() - Method in class edu.cmu.minorthird.util.gui.ViewerControls: Add an update button.
addBinary(Feature) - Method in class edu.cmu.minorthird.classify.MutableInstance: Add a binary feature.
addCandidateSegmentGroup(CandidateSegmentGroup) - Method in class edu.cmu.minorthird.classify.sequential.SegmentDataset: Add a new sequence of examples to the dataset.
addDocument(String, String) - Method in class edu.cmu.minorthird.text.learn.OnlineBinaryTextClassifierLearner: Provide document string with a label and add to the learner
addDocument(String, String) - Method in interface edu.cmu.minorthird.text.learn.OnlineTextClassifierLearner: Provide document string with a label and add to the learner
AddDocuments() - Method in class edu.cmu.minorthird.text.gui.OnlineClassifierDocumentEditor: Adds all the documents that have been edited but not already added to the classifier
added - Variable in class edu.cmu.minorthird.text.gui.OnlineClassifierDocumentEditor.EditedSpan
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.active.QueryByCommittee
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.knn.KnnLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.BalancedWinnow
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.BBMira
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.KernelVotedPerceptron
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.MarginPerceptron
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.NaiveBayes
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.PassiveAggressiveLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.RegretWinnow
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.ROMMALearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.VitorBalancedWinnow
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.VotedPerceptron
addExample(Example) - Method in class edu.cmu.minorthird.classify.algorithms.linear.Winnow
addExample(Example) - Method in class edu.cmu.minorthird.classify.BatchClassifierLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.CascadingBinaryLearner
addExample(Example) - Method in interface edu.cmu.minorthird.classify.ClassifierLearner: Accept a labeled example.
addExample(Example) - Method in class edu.cmu.minorthird.classify.DatasetIndex: Add a single example to the index.
addExample(Example) - Method in interface edu.cmu.minorthird.classify.FeatureIndex
addExample(Example) - Method in class edu.cmu.minorthird.classify.ManyVsRestLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.MistakeCountingOnlineLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.multi.MultiLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.OneVsAllLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.OnlineClassifierLearner: Subclasses should use this method to perform whatever incremental update is needed after in response to a new example.
addExample(Example) - Method in class edu.cmu.minorthird.classify.OnlineVersion
addExample(Example) - Method in class edu.cmu.minorthird.classify.relational.StackedBatchClassifierLearner
addExample(Example) - Method in class edu.cmu.minorthird.classify.semisupervised.SemiSupervisedBatchClassifierLearner
addFeature(double, Feature) - Method in class edu.cmu.minorthird.classify.transform.ChiSquareInstanceTransform: Adds a score of feature f to the InstanceTransform
addFeature(String, String, String, StringBuffer) - Static method in class edu.cmu.minorthird.util.LineProcessingUtil: If the line substring matches the regexp, it adds a " featurename=1" to the string buffer It is useful for producing external datasets in Minorthird format
addFeatureIG(double, Feature) - Method in class edu.cmu.minorthird.classify.transform.InfoGainInstanceTransform: Adds the Info-Gain score of feature f to the InstanceTransform
addFeatureVal(double, Feature) - Method in class edu.cmu.minorthird.classify.transform.OrderBasedInstanceTransform: Adds the Info-Gain score of feature f to the InstanceTransform
addLink(Link) - Static method in class edu.cmu.minorthird.classify.relational.CoreRelationalDataset: Add a link to the LinksMap of the dataset.
addMulti(MultiExample) - Method in class edu.cmu.minorthird.classify.multi.MultiDataset
addMultiExample(MultiExample) - Method in class edu.cmu.minorthird.classify.multi.MultiDatasetIndex: Add a single example to the index.
addMultiExample(MultiExample) - Method in class edu.cmu.minorthird.classify.multi.MultiLearner
addNumeric(Feature, double) - Method in class edu.cmu.minorthird.classify.MutableInstance: Add a numeric feature.
addPoint(double, double, boolean) - Method in class edu.cmu.minorthird.util.gui.LineCharter: Add a point to the current curve.
addPoint(double, double) - Method in class edu.cmu.minorthird.util.gui.LineCharter: Add a point to the current curve.
addSequence(Example[]) - Method in class edu.cmu.minorthird.classify.sequential.SequenceDataset: Add a new sequence of examples to the dataset.
addSequence(Example[], boolean) - Method in class edu.cmu.minorthird.classify.sequential.SequenceDataset: Add a new sequence of examples to the dataset

This method allows the caller to specify if they want the examples to be compressed or not.
addSGM(SGMExample) - Method in class edu.cmu.minorthird.classify.relational.CoreRelationalDataset
addSGM(SGMExample, boolean) - Method in class edu.cmu.minorthird.classify.relational.CoreRelationalDataset: Add an Example to the dataset.
addStatement(Mixup.MixupTokenizer, String) - Method in class edu.cmu.minorthird.text.mixup.MixupProgram: Add a single statement to the current mixup program.
addStatement(String) - Method in class edu.cmu.minorthird.text.mixup.MixupProgram: Add a single statement to the current mixup program.
addSubView(String, Viewer) - Method in class edu.cmu.minorthird.util.gui.ParallelViewer: Add a new way of viewing the content object.
addToType(Span, String) - Method in class edu.cmu.minorthird.text.BasicTextLabels
addToType(Span, String, Details) - Method in class edu.cmu.minorthird.text.BasicTextLabels
addToType(Span, String) - Method in class edu.cmu.minorthird.text.learn.experiments.MonotonicSubTextLabels
addToType(Span, String, Details) - Method in class edu.cmu.minorthird.text.learn.experiments.MonotonicSubTextLabels
addToType(Span, String) - Method in interface edu.cmu.minorthird.text.MonotonicTextLabels: Assert that a span has a given type.
addToType(Span, String, Details) - Method in interface edu.cmu.minorthird.text.MonotonicTextLabels: Assert that a span has a given type, and associate that assertion with some detailed information.
addToType(Span, String) - Method in class edu.cmu.minorthird.text.NestedTextLabels
addToType(Span, String, Details) - Method in class edu.cmu.minorthird.text.NestedTextLabels
addUnlabeled(Instance) - Method in class edu.cmu.minorthird.classify.BasicDataset
addUnlabeled(Instance) - Method in class edu.cmu.minorthird.classify.multi.MultiDataset
addUnlabeled(Instance) - Method in interface edu.cmu.minorthird.classify.semisupervised.SemiSupervisedActions: Add a new semisupervised example to the dataset.
addUnlabeled(Instance) - Method in class edu.cmu.minorthird.classify.semisupervised.SemiSupervisedDataset
addValidLabel(ClassLabel) - Method in class edu.cmu.minorthird.classify.algorithms.linear.MultinomialClassifier
addValidLabel(ClassLabel) - Method in class edu.cmu.minorthird.classify.semisupervised.MultinomialClassifier
addViewer(TextBaseViewer) - Method in class edu.cmu.minorthird.text.gui.SpanLabeler: Say where the viewer is..
addWords(String, String[]) - Method in class edu.cmu.minorthird.text.Trie: Associate a sequence of words with a given id.
advance() - Method in class edu.cmu.minorthird.text.mixup.Mixup.MixupTokenizer
advance(Set<String>) - Method in class edu.cmu.minorthird.text.mixup.Mixup.MixupTokenizer
advancedParameters - Class in edu.cmu.minorthird.ui: Defines the list of classes that can be selected by an instance of UIMain.
advancedParameters() - Constructor for class edu.cmu.minorthird.ui.advancedParameters
aggregators - Static variable in class edu.cmu.minorthird.classify.relational.RealRelationalDataset
alpha - Variable in class edu.cmu.minorthird.classify.algorithms.random.Gamma
AlphaSigma(double, double, double[], double[], double, double, double, double, double[], double, double, double) - Static method in class edu.cmu.minorthird.classify.algorithms.random.ProbabilityFactory
AlphaTau(double, double, double[], double[], double, double, double, double, double[], double, double, double) - Static method in class edu.cmu.minorthird.classify.algorithms.random.ProbabilityFactory
ann - Variable in class edu.cmu.minorthird.text.gui.OnlineClassifierDocumentEditor
annotate(MonotonicTextLabels) - Method in class edu.cmu.minorthird.text.AbstractAnnotator
annotate(MonotonicTextLabels) - Method in interface edu.cmu.minorthird.text.Annotator: Add some extra information to the labels.
annotate(String) - Method in class edu.cmu.minorthird.text.LabeledDirectory.MyCLP
ANNOTATE_WITH - Static variable in class edu.cmu.minorthird.text.mixup.Statement
annotateData() - Method in class edu.cmu.minorthird.classify.multi.MultiDataset
annotateData(MultiClassifier) - Method in class edu.cmu.minorthird.classify.multi.MultiDataset
annotateData(MultiClassifier, MultiDataset) - Method in class edu.cmu.minorthird.classify.Test.DataClassificationTask
annotateData(MultiDataset) - Method in class edu.cmu.minorthird.classify.Train.DataClassificationTask
annotateData(MultiClassifier, MultiDataset) - Method in class edu.cmu.minorthird.classify.TrainTest.DataClassificationTask
annotateData(MultiClassifier, MultiDataset) - Method in class edu.cmu.minorthird.classify.UI.DataClassificationTask
annotatedCopy(TextLabels) - Method in class edu.cmu.minorthird.text.AbstractAnnotator
annotatedCopy(TextLabels) - Method in interface edu.cmu.minorthird.text.Annotator: Create a copy of the labels with some additional information added.
annotatedCopy(TextLabels) - Method in interface edu.cmu.minorthird.text.learn.OnlineTextClassifierLearner: Returns an annotated copy of TextLabels
annotatedLabels - Variable in class edu.cmu.minorthird.ui.RunMixup
annotateString(String) - Method in class edu.cmu.minorthird.text.MinorTagger
annotateString(String) - Method in class edu.cmu.minorthird.text.POSTagger: Returns char based stand-off annotations for pos in the given string This will not work with html/xml in the string!
annotateString(String) - Method in class edu.cmu.minorthird.text.StringAnnotator: Override this class to provide the actual annotations for a span.
annotateWith(String, String) - Method in class edu.cmu.minorthird.text.BasicTextLabels
annotateWith(MonotonicTextLabels, String, String) - Static method in class edu.cmu.minorthird.text.BasicTextLabels
annotateWith(String, String) - Method in class edu.cmu.minorthird.text.EmptyLabels
annotateWith(String, String) - Method in class edu.cmu.minorthird.text.learn.experiments.SubTextLabels: Annotate labels with annotator named fileToLoad
annotateWith(String, String) - Method in class edu.cmu.minorthird.text.NestedTextLabels: Annotate labels with annotator named fileToLoad
annotateWith(String, String) - Method in interface edu.cmu.minorthird.text.TextLabels: Annotate labels with annotator named fileToLoad
AnnotationExample - Class in edu.cmu.minorthird.text.learn: Feedback for an annotation learner.
AnnotationExample(Span, TextLabels, String, String) - Constructor for class edu.cmu.minorthird.text.learn.AnnotationExample
annotationType - Variable in class edu.cmu.minorthird.text.learn.AbstractBatchAnnotatorLearner
annotationType - Variable in class edu.cmu.minorthird.text.learn.SegmentAnnotatorLearner
Annotator - Interface in edu.cmu.minorthird.text: Something that extends a text labeling with additional annotations.
AnnotatorLearner - Class in edu.cmu.minorthird.text.learn: Learn an Annotator from AnnotationExample's.
AnnotatorLearner() - Constructor for class edu.cmu.minorthird.text.learn.AnnotatorLearner
AnnotatorLoader - Class in edu.cmu.minorthird.text: Analogous to a ClassLoader, this finds annotators by name, so they can be applied to a set of labels.
AnnotatorLoader() - Constructor for class edu.cmu.minorthird.text.AnnotatorLoader
annotatorLoader - Variable in class edu.cmu.minorthird.text.learn.SpanFE
AnnotatorTeacher - Class in edu.cmu.minorthird.text.learn: Train a AnnotatorLearner and return the learned Annotator, using some unspecified source of information to get AnnotationExample's to train the learner.
AnnotatorTeacher() - Constructor for class edu.cmu.minorthird.text.learn.AnnotatorTeacher
append(String) - Method in class edu.cmu.minorthird.util.gui.Console: Append a string to the console window.
apply(T) - Method in class edu.cmu.minorthird.text.learn.SpanFE.Function: Should return the modified object.
ApplyAnnotator - Class in edu.cmu.minorthird.ui: Apply a serialized annotator.
ApplyAnnotator() - Constructor for class edu.cmu.minorthird.ui.ApplyAnnotator
applyControls(ViewerControls) - Method in class edu.cmu.minorthird.text.gui.SpanViewer
applyControls(ViewerControls) - Method in class edu.cmu.minorthird.text.gui.SpanViewer.TextViewer
applyControls(ViewerControls) - Method in class edu.cmu.minorthird.text.gui.TextLabelsViewer
applyControls(ViewerControls) - Method in interface edu.cmu.minorthird.util.gui.Controllable
applyFilter(SpanFE.Filter) - Method in class edu.cmu.minorthird.text.learn.SpanFE.SetResult: Filter the set using a user-defined filter.
Arithmetic - Class in edu.cmu.minorthird.classify.algorithms.random
Arithmetic() - Constructor for class edu.cmu.minorthird.classify.algorithms.random.Arithmetic
asBag() - Method in class edu.cmu.minorthird.text.learn.SpanFE.StringBagResult
asInstance() - Method in class edu.cmu.minorthird.classify.Example: Return an unlabeled version of the example (an Instance)
asPlainInstance() - Method in class edu.cmu.minorthird.classify.multi.InstanceFromPrediction: Return the wrapped instance.
asPlainInstance() - Method in class edu.cmu.minorthird.classify.sequential.InstanceFromSequence: Return the wrapped instance.
asSet() - Method in class edu.cmu.minorthird.classify.WeightedSet
asSet() - Method in class edu.cmu.minorthird.text.learn.SpanFE.SetResult: Convert to a plain old set.
assignDefaultLabels(Span, MonotonicTextLabels, String, String) - Method in class edu.cmu.minorthird.text.learn.Extraction2TaggingReduction: Label all tokens as negative, including ones which are inside a span to be extracted.
asString() - Method in class edu.cmu.minorthird.text.BasicSpan: Find the string contained in a Span.
asString() - Method in interface edu.cmu.minorthird.text.Span: Find the string contained in a Span.
asString() - Method in class edu.cmu.minorthird.text.TextToken
atof(String) - Static method in class edu.cmu.minorthird.util.StringUtil: Convert a string to a double.
atoi(String) - Static method in class edu.cmu.minorthird.util.StringUtil: Convert a string to an integer.
AtoZPercentage(String) - Static method in class edu.cmu.minorthird.util.LineProcessingUtil: Returns the percentage of A-Z or a-z characters in a line
AugmentedInstance - Class in edu.cmu.minorthird.classify.transform: Add some features to an instance.
AugmentedInstance(Instance, String[], double[]) - Constructor for class edu.cmu.minorthird.classify.transform.AugmentedInstance
AugmentedInstance.MyIterator - Class in edu.cmu.minorthird.classify.transform
AugmentedInstance.MyIterator() - Constructor for class edu.cmu.minorthird.classify.transform.AugmentedInstance.MyIterator
author() - Method in class edu.cmu.minorthird.text.Details
availableLabels() - Method in class edu.cmu.minorthird.text.learn.AnnotatorTeacher: Labels available for training, testing
availableLabels() - Method in class edu.cmu.minorthird.text.learn.TextLabelsAnnotatorTeacher
averageElevenPointPrecision() - Method in class edu.cmu.minorthird.classify.ranking.RankingEvaluation: Interpolated precision at eleven recall levels, averaged over all examples.
averageFeaturesPerExample() - Method in class edu.cmu.minorthird.classify.DatasetIndex: Average number of non-zero feature values in examples.
averageFeaturesPerExample() - Method in class edu.cmu.minorthird.classify.multi.MultiDatasetIndex: Average number of non-zero feature values in examples.
averageLogLoss() - Method in class edu.cmu.minorthird.classify.experiments.Evaluation: Average logloss on all examples.
averagePrecision() - Method in class edu.cmu.minorthird.classify.experiments.Evaluation: Non-interpolated average precision.
averagePrecision(String) - Method in class edu.cmu.minorthird.classify.ranking.RankingEvaluation: Non-interpolated average precision.
averageRecallAsFunctionOfK() - Method in class edu.cmu.minorthird.classify.ranking.RankingEvaluation: Recall as function of K, averaged over all examples.

B

Backward - Class in edu.cmu.minorthird.classify.sequential
Backward(HMM, String[]) - Constructor for class edu.cmu.minorthird.classify.sequential.Backward
BAG_OF_LC_WORDS - Static variable in class edu.cmu.minorthird.text.learn.SampleFE: Simple bag of words feature extractor, with all tokens converted to lower case.
BAG_OF_WORDS - Static variable in class edu.cmu.minorthird.text.learn.SampleFE: Simple bag of words feature extractor.
BalancedWinnow - Class in edu.cmu.minorthird.classify.algorithms.linear: Created on Sep 22, 2005
BalancedWinnow() - Constructor for class edu.cmu.minorthird.classify.algorithms.linear.BalancedWinnow
BalancedWinnow(boolean) - Constructor for class edu.cmu.minorthird.classify.algorithms.linear.BalancedWinnow: Constructor: voted="true" (more stable) or "false"(more aggressive)
BalancedWinnow(double, double, boolean) - Constructor for class edu.cmu.minorthird.classify.algorithms.linear.BalancedWinnow
BalancedWinnow.MyClassifier - Class in edu.cmu.minorthird.classify.algorithms.linear
BalancedWinnow.MyClassifier(Hyperplane, Hyperplane, double) - Constructor for class edu.cmu.minorthird.classify.algorithms.linear.BalancedWinnow.MyClassifier
base - Variable in class edu.cmu.minorthird.classify.ClassifyCommandLineUtil.TestParams
base - Variable in class edu.cmu.minorthird.classify.ClassifyCommandLineUtil.TrainTestParams
base - Variable in class edu.cmu.minorthird.text.gui.TrackedTextBaseComponent
base - Variable in class edu.cmu.minorthird.ui.UIMain
base - Variable in class edu.cmu.minorthird.ui.ViewLabels
BasicCommandLineProcessor - Class in edu.cmu.minorthird.util: A lightweight command-line processing tool.
BasicCommandLineProcessor() - Constructor for class edu.cmu.minorthird.util.BasicCommandLineProcessor
BasicDataset - Class in edu.cmu.minorthird.classify: A set of examples for learning.
BasicDataset(FeatureFactory) - Constructor for class edu.cmu.minorthird.classify.BasicDataset
BasicDataset() - Constructor for class edu.cmu.minorthird.classify.BasicDataset
BasicDataset.SimpleDatasetViewer - Class in edu.cmu.minorthird.classify
BasicDataset.SimpleDatasetViewer() - Constructor for class edu.cmu.minorthird.classify.BasicDataset.SimpleDatasetViewer
BasicFeatureIndex - Class in edu.cmu.minorthird.classify
BasicFeatureIndex() - Constructor for class edu.cmu.minorthird.classify.BasicFeatureIndex
BasicFeatureIndex(Dataset) - Constructor for class edu.cmu.minorthird.classify.BasicFeatureIndex
BasicSpan - Class in edu.cmu.minorthird.text: Implements the Span interface.
BasicSpan(String, TextToken[], int, int, String) - Constructor for class edu.cmu.minorthird.text.BasicSpan: Constructor assumes that the textTokens are all from the documentId.
BasicTextBase - Class in edu.cmu.minorthird.text: Maintains information about what's in a set of documents.
BasicTextBase() - Constructor for class edu.cmu.minorthird.text.BasicTextBase: Default constructor creates a new TextBase with the default Tokenizer.
BasicTextBase(Tokenizer) - Constructor for class edu.cmu.minorthird.text.BasicTextBase: Constructor that specifies a custom Tokenizer to be used with this TextBase.
BasicTextLabels - Class in edu.cmu.minorthird.text: Maintains assertions about 'types' and 'properties' of contiguous Spans of these TextToken's.
BasicTextLabels() - Constructor for class edu.cmu.minorthird.text.BasicTextLabels: Creates an empty TextLabels not associated with a TextBase
BasicTextLabels(TextBase) - Constructor for class edu.cmu.minorthird.text.BasicTextLabels: Creates an empty TextLabels associated with the specified TextBase
BasicTextLabels(String) - Constructor for class edu.cmu.minorthird.text.BasicTextLabels: A convenience method which creates empty labels containing a single string.
BatchBinaryClassifierLearner - Class in edu.cmu.minorthird.classify: Simple abstract class, getBinaryClassifier() method for a BinaryClassifierLearner, and also a batchTrainBinary() method.
BatchBinaryClassifierLearner() - Constructor for class edu.cmu.minorthird.classify.BatchBinaryClassifierLearner
BatchClassifierLearner - Class in edu.cmu.minorthird.classify: Abstract ClassifierLearner which instantiates the teacher-learner protocol so as to implement a standard batch learner.
BatchClassifierLearner() - Constructor for class edu.cmu.minorthird.classify.BatchClassifierLearner
BatchRankingLearner - Class in edu.cmu.minorthird.classify.ranking: Learns to rank sets of examples, rather than to classify individual examples.
BatchRankingLearner() - Constructor for class edu.cmu.minorthird.classify.ranking.BatchRankingLearner
BatchSegmenterLearner - Interface in edu.cmu.minorthird.classify.sequential
BatchSequenceClassifierLearner - Interface in edu.cmu.minorthird.classify.sequential: A SequenceClassifierLearner that trains itself in batch mode.
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.linear.KWayMixtureLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.linear.MaxEntLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.linear.NegativeBinomialLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.linear.PoissonLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.svm.SVMLearner: Train a classifier using the given dataset.
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.trees.AdaBoost
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.trees.DecisionTreeLearner
batchTrain(List<Example>, Vector<Feature>) - Method in class edu.cmu.minorthird.classify.algorithms.trees.FastRandomTreeLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.trees.FastRandomTreeLearner
batchTrain(Vector<Example>, int, Vector<Feature>, int, int, int) - Method in class edu.cmu.minorthird.classify.algorithms.trees.FastRandomTreeLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.trees.RandomForests
batchTrain(List<Example>, Vector<Feature>) - Method in class edu.cmu.minorthird.classify.algorithms.trees.RandomTreeLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.algorithms.trees.RandomTreeLearner
batchTrain(List<Example>, int, Vector<Feature>) - Method in class edu.cmu.minorthird.classify.algorithms.trees.RandomTreeLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.BatchClassifierLearner: subclasses should use this method to implement a batch supervised learning algorithm.
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.BatchVersion
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.ranking.ListNet
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.ranking.RankingBoosted
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.ranking.RankingPerceptron
batchTrain(RealRelationalDataset) - Method in class edu.cmu.minorthird.classify.relational.StackedBatchClassifierLearner: subclasses should use this method to implement a batch supervised learning algorithm.
batchTrain(RealRelationalDataset) - Method in class edu.cmu.minorthird.classify.relational.StackedGraphicalLearner
batchTrain(SemiSupervisedDataset) - Method in class edu.cmu.minorthird.classify.semisupervised.SemiSupervisedBatchClassifierLearner: subclasses should use this method to implement a batch supervised learning algorithm.
batchTrain(SemiSupervisedDataset) - Method in class edu.cmu.minorthird.classify.semisupervised.SemiSupervisedNaiveBayesLearner
batchTrain(SegmentDataset) - Method in interface edu.cmu.minorthird.classify.sequential.BatchSegmenterLearner
batchTrain(SequenceDataset) - Method in interface edu.cmu.minorthird.classify.sequential.BatchSequenceClassifierLearner
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.CMMLearner
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.CollinsPerceptronLearner
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.CRFLearner
batchTrain(SegmentDataset) - Method in class edu.cmu.minorthird.classify.sequential.DictVersion
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.GenericCollinsLearner
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.GenericCollinsLearnerV1
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.HMMLearner
batchTrain(SegmentDataset) - Method in class edu.cmu.minorthird.classify.sequential.LeaveOneOutDictVersion
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.MarginPerceptronLearner
batchTrain(SegmentDataset) - Method in class edu.cmu.minorthird.classify.sequential.SegmentCollinsPerceptronLearner
batchTrain(SegmentDataset) - Method in class edu.cmu.minorthird.classify.sequential.SegmentCRFLearner
batchTrain(SegmentDataset) - Method in class edu.cmu.minorthird.classify.sequential.SegmentGenericCollinsLearner
batchTrain(SequenceDataset) - Method in class edu.cmu.minorthird.classify.sequential.StackedSequenceLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.StackedLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.ChiSquareTransformLearner: Examine data, build an instance transformer
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.D2TransformLearner: Examine data, build an instance transformer
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.FrequencyBasedTransformLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.InfoGainTransformLearner: Examine data, build an instance transformer
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.InfoGainTransformLearner2
batchTrain(Dataset) - Method in interface edu.cmu.minorthird.classify.transform.InstanceTransformLearner: Examine data, build an instance transformer
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.LeaveOneOutDictTransformLearner: Examine data, build an instance transformer
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.MakeBinaryTransform
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.OrderBasedTransformLearner: Examine data, build an instance transformer
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.T1InstanceTransformLearner: Examine data, build an instance transformer
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.TFIDFTransformLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.transform.TransformingBatchLearner
batchTrain(Dataset) - Method in class edu.cmu.minorthird.classify.TweakedLearner
batchTrainBinary(Dataset) - Method in class edu.cmu.minorthird.classify.BatchBinaryClassifierLearner: Train a binary classifier.
batchTrainCommittee(RandomAccessDataset) - Method in class edu.cmu.minorthird.classify.algorithms.active.CommitteeLearner: Learn a committee
BatchVersion - Class in edu.cmu.minorthird.classify: Batch version of an OnlineClassifierLearner.
BatchVersion(OnlineClassifierLearner, int) - Constructor for class edu.cmu.minorthird.classify.BatchVersion
BatchVersion(OnlineClassifierLearner) - Constructor for class edu.cmu.minorthird.classify.BatchVersion
BatchVersion() - Constructor for class edu.cmu.minorthird.classify.BatchVersion
baumwelch(ArrayList<String[]>, String[], Hashtable<String, String>, double) - Static method in class edu.cmu.minorthird.classify.sequential.HMM
baumwelch(double) - Method in class edu.cmu.minorthird.classify.sequential.MultiClassHMMClassifier
BBMira - Class in edu.cmu.minorthird.classify.algorithms.linear: A budgeted version of binary MIRA.
BBMira(boolean, double) - Constructor for class edu.cmu.minorthird.classify.algorithms.linear.BBMira
BBMira() - Constructor for class edu.cmu.minorthird.classify.algorithms.linear.BBMira
BeamSearcher - Class in edu.cmu.minorthird.classify.sequential: A conditional markov model classifier.
BeamSearcher(Classifier, int, ExampleSchema) - Constructor for class edu.cmu.minorthird.classify.sequential.BeamSearcher
BeginContinueEndUniqueReduction - Class in edu.cmu.minorthird.text.learn: Reducing an extraction task to tagging tokens as one of five categories.
BeginContinueEndUniqueReduction() - Constructor for class edu.cmu.minorthird.text.learn.BeginContinueEndUniqueReduction
BeginContinueOutsideReduction - Class in edu.cmu.minorthird.text.learn: Reduces an extraction task to tagging tokens as one of three categories.
BeginContinueOutsideReduction() - Constructor for class edu.cmu.minorthird.text.learn.BeginContinueOutsideReduction
bestClassName() - Method in class edu.cmu.minorthird.classify.ClassLabel: Returns the highest-ranking label.
bestClassName() - Method in class edu.cmu.minorthird.classify.multi.MultiClassLabel: Returns the highest-ranking label.
bestLabelSequence(Instance[]) - Method in class edu.cmu.minorthird.classify.sequential.BeamSearcher: Get the best label sequence, as determined by the beam search
bestSegments(CandidateSegmentGroup) - Method in class edu.cmu.minorthird.classify.sequential.SegmentCollinsPerceptronLearner.ViterbiSearcher
bestSegments(Span, TextLabels, SpanFeatureExtractor, BinaryClassifier, int) - Static method in class edu.cmu.minorthird.text.learn.ConditionalSemiMarkovModel
bestWeight() - Method in class edu.cmu.minorthird.classify.ClassLabel: Returns the weight of the highest-ranking label.
bestWeight() - Method in class edu.cmu.minorthird.classify.multi.MultiClassLabel: Returns the weight of the highest-ranking label.
beta(String) - Method in class edu.cmu.minorthird.text.learn.ExtractorTweaker.MyCLP
BIAS_TERM - Static variable in class edu.cmu.minorthird.classify.algorithms.linear.Hyperplane: Weight for an invisible 'bias feature' which is considered to be present in every instance.
big - Static variable in class edu.cmu.minorthird.classify.algorithms.random.Constants
biginv - Static variable in class edu.cmu.minorthird.classify.algorithms.random.Constants
BINARY_EXAMPLE_SCHEMA - Static variable in class edu.cmu.minorthird.classify.ExampleSchema: Schema for binary examples.
BinaryBatchVersion - Class in edu.cmu.minorthird.classify: Batch version of an OnlineBinaryClassifierLearner
BinaryBatchVersion(OnlineBinaryClassifierLearner, int) - Constructor for class edu.cmu.minorthird.classify.BinaryBatchVersion
BinaryBatchVersion(OnlineBinaryClassifierLearner) - Constructor for class edu.cmu.minorthird.classify.BinaryBatchVersion
BinaryClassifier - Class in edu.cmu.minorthird.classify: A Classifier which associates instances with a real number.
BinaryClassifier() - Constructor for class edu.cmu.minorthird.classify.BinaryClassifier
BinaryClassifierLearner - Interface in edu.cmu.minorthird.classify: Learn a BinaryClassifier.
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.Example: Return an iterator over all binary features
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.FeatureFactory.CompactInstance
binaryFeatureIterator() - Method in interface edu.cmu.minorthird.classify.Instance: Return an iterator over all binary features.
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.multi.InstanceFromPrediction
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.MutableInstance: Return an iterator over all binary features
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.sequential.HyperplaneInstance
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.sequential.InstanceFromSequence
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.transform.AugmentedInstance
binaryFeatureIterator() - Method in class edu.cmu.minorthird.classify.transform.