Uses of Class
de.fu_berlin.ties.classify.feature.FeatureVector

Packages that use FeatureVector
de.fu_berlin.ties.classify This package provides functionality for classification of texts and feature vectors. 
de.fu_berlin.ties.classify.feature This package contains classes for working with features, feature vectors and feature transformers. 
de.fu_berlin.ties.classify.winnow This package contains the Winnow classification algorithm and related algorithms and classes. 
de.fu_berlin.ties.context This packages provides functionality for building and managing representations of context in texts (XML documents). 
de.fu_berlin.ties.eval This packages provides functionality for evaluating results of classifiers and extractors. 
de.fu_berlin.ties.extract This package handles information extraction and entitiy recognition. 
de.fu_berlin.ties.extract.amend This package provides code for reanalysing proposed extractions and performing suitable amendments to improve results. 
de.fu_berlin.ties.filter This packages provides generic filtering functionality and an implementation for sentence filtering. 
 

Uses of FeatureVector in de.fu_berlin.ties.classify
 

Methods in de.fu_berlin.ties.classify with parameters of type FeatureVector
 PredictionDistribution TrainableClassifier.classify(FeatureVector features, Set candidateClasses)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes.
 PredictionDistribution Classifier.classify(FeatureVector features, Set candidateClasses)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes.
protected  PredictionDistribution MetaClassifier.doClassify(FeatureVector features, Set candidateClasses, ContextMap context)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes.
protected  PredictionDistribution OneAgainstTheRestClassifier.doClassify(FeatureVector features, Set candidateClasses, ContextMap context)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes. This implementation combines the predictions for the positive class of all involved inner classifiers.
protected  PredictionDistribution ExternalClassifier.doClassify(FeatureVector features, Set candidateClasses, ContextMap context)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes.
protected abstract  PredictionDistribution TrainableClassifier.doClassify(FeatureVector features, Set candidateClasses, ContextMap context)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes.
protected  PredictionDistribution MultiBinaryClassifier.doClassify(FeatureVector features, Set candidateClasses, ContextMap context)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes. This implementation combines the predictions for the foreground of all involved inner classifiers.
protected  void MetaClassifier.doTrain(FeatureVector features, String targetClass, ContextMap context)
          Incorporates an item that is represented by a feature vector into the classification model.
protected  void OneAgainstTheRestClassifier.doTrain(FeatureVector features, String targetClass, ContextMap context)
          Incorporates an item that is represented by a feature vector into the classification model.
protected  void ExternalClassifier.doTrain(FeatureVector features, String targetClass, ContextMap context)
          Incorporates an item that is represented by a feature vector into the classification model.
protected abstract  void TrainableClassifier.doTrain(FeatureVector features, String targetClass, ContextMap context)
          Incorporates an item that is represented by a feature vector into the classification model.
protected  void MultiBinaryClassifier.doTrain(FeatureVector features, String targetClass, ContextMap context)
          Incorporates an item that is represented by a feature vector into the classification model.
 void TrainableClassifier.train(FeatureVector features, String targetClass)
          Incorporates an item that is represented by a feature vector into the classification model.
 PredictionDistribution TrainableClassifier.trainOnError(FeatureVector features, String targetClass, Set candidateClasses)
          Handles error-driven learning ("train only errors"): the specified feature vector is trained into the model only if the predicted class for the feature vector differs from the specified target class.
protected  boolean MetaClassifier.trainOnErrorHook(PredictionDistribution predDist, FeatureVector features, String targetClass, Set candidateClasses, ContextMap context)
          Subclasses can implement this hook for more refined error-driven learning.
protected  boolean OneAgainstTheRestClassifier.trainOnErrorHook(PredictionDistribution predDist, FeatureVector features, String targetClass, Set candidateClasses, ContextMap context)
          Subclasses can implement this hook for more refined error-driven learning.
protected  boolean TrainableClassifier.trainOnErrorHook(PredictionDistribution predDist, FeatureVector features, String targetClass, Set candidateClasses, ContextMap context)
          Subclasses can implement this hook for more refined error-driven learning.
protected  boolean MultiBinaryClassifier.trainOnErrorHook(PredictionDistribution predDist, FeatureVector features, String targetClass, Set candidateClasses, ContextMap context)
          Subclasses can implement this hook for more refined error-driven learning.
 

Uses of FeatureVector in de.fu_berlin.ties.classify.feature
 

Subclasses of FeatureVector in de.fu_berlin.ties.classify.feature
 class DefaultFeatureVector
          This feature vector implementation stores an ordered sequence of features.
 class FeatureSet
          This feature vector implementation stores a multi-set of features.
 

Methods in de.fu_berlin.ties.classify.feature that return FeatureVector
protected  FeatureVector OSBTransformer.doTransform(FeatureVector orgFeatures)
          Transforms a feature vector.
protected  FeatureVector SBPHTransformer.doTransform(FeatureVector orgFeatures)
          Transforms a feature vector.
protected abstract  FeatureVector FeatureTransformer.doTransform(FeatureVector orgFeatures)
          Transforms a feature vector.
 FeatureVector FeatureTransformer.transform(FeatureVector orgFeatures)
          Transforms a feature vector.
 

Methods in de.fu_berlin.ties.classify.feature with parameters of type FeatureVector
 void FeatureVector.addAll(FeatureVector fv)
          Adds all of the features in the specified feature vector to this vector, in the order they are returned by the specified feature vector.
protected  FeatureVector OSBTransformer.doTransform(FeatureVector orgFeatures)
          Transforms a feature vector.
protected  FeatureVector SBPHTransformer.doTransform(FeatureVector orgFeatures)
          Transforms a feature vector.
protected abstract  FeatureVector FeatureTransformer.doTransform(FeatureVector orgFeatures)
          Transforms a feature vector.
 FeatureVector FeatureTransformer.transform(FeatureVector orgFeatures)
          Transforms a feature vector.
 

Uses of FeatureVector in de.fu_berlin.ties.classify.winnow
 

Methods in de.fu_berlin.ties.classify.winnow with parameters of type FeatureVector
protected  PredictionDistribution Winnow.doClassify(FeatureVector features, Set candidateClasses, ContextMap context)
          Classifies an item that is represented by a feature vector by choosing the most probable class among a set of candidate classes.
protected  void Winnow.doTrain(FeatureVector features, String targetClass, ContextMap context)
          Winnow supports only error-driven training, so you always have to use the TrainableClassifier.trainOnError(FeatureVector, String, Set) method instead of this one.
protected  FeatureSet Winnow.featureSet(FeatureVector fv)
          Converts a feature vector into a FeatureSet (a multi-set of features).
protected  boolean Winnow.trainOnErrorHook(PredictionDistribution predDist, FeatureVector features, String targetClass, Set candidateClasses, ContextMap context)
          Hook implementing error-driven learning, promoting and demoting weights as required.
 

Uses of FeatureVector in de.fu_berlin.ties.context
 

Methods in de.fu_berlin.ties.context that return FeatureVector
 FeatureVector Representation.buildContext(Document document, PriorRecognitions priorRecognitions, Map<Element,List<LocalFeature>> featureCache, String logPurpose)
          Builds the context representation of a document.
 FeatureVector Representation.buildContext(Element element, PriorRecognitions priorRecognitions, Map<Element,List<LocalFeature>> featureCache, String logPurpose)
          Builds the context representation of an element.
abstract  FeatureVector Representation.buildContext(Element element, String leftText, String mainText, String rightText, PriorRecognitions priorRecognitions, Map<Element,List<LocalFeature>> featureCache, String logPurpose)
          Builds the context representation of text in an element.
 FeatureVector AbstractRepresentation.buildContext(Element element, String leftText, String mainText, String rightText, PriorRecognitions priorRecognitions, Map<Element,List<LocalFeature>> featureCache, String logPurpose)
          Builds the context representation of text in an element.
protected  FeatureVector DefaultRepresentation.doBuildContext(Element element, String leftText, String mainText, String rightText, PriorRecognitions priorRecognitions, Map<Element,List<LocalFeature>> featureCache, String logPurpose)
          Builds the context representation of text in an element.
protected abstract  FeatureVector AbstractRepresentation.doBuildContext(Element element, String leftText, String mainText, String rightText, PriorRecognitions priorRecognitions, Map<Element,List<LocalFeature>> featureCache, String logPurpose)
          Builds the context representation of text in an element.
protected  FeatureVector SimpleRepresentation.doBuildContext(Element element, String leftText, String mainText, String rightText, PriorRecognitions priorRecognitions, Map featureCache, String logPurpose)
          Builds the context representation of text in an element.
 

Methods in de.fu_berlin.ties.context with parameters of type FeatureVector
protected  void SimpleRepresentation.addFeature(FeatureVector features, String prefix, String value)
          Creates a feature and adds it to a feature vector.
protected  void SimpleRepresentation.addText(FeatureVector features, String prefix, String text)
          Adds feature(s) representing text to a feature vector, using the instance tokenizer for splitting the text into tokens.
protected  List<Feature> DefaultRepresentation.filterRepresentation(FeatureVector originalRep)
          Creates a filtered view of a context representation.
 

Uses of FeatureVector in de.fu_berlin.ties.eval
 

Methods in de.fu_berlin.ties.eval with parameters of type FeatureVector
 void FeatureCount.update(FeatureVector features)
          Evaluates a feature vector and updates the statistics accordingly.
 

Uses of FeatureVector in de.fu_berlin.ties.extract
 

Methods in de.fu_berlin.ties.extract that return FeatureVector
protected  FeatureVector ExtractorBase.getFeatures()
          Returns vector of features representing the currently processed element.
 

Uses of FeatureVector in de.fu_berlin.ties.extract.amend
 

Methods in de.fu_berlin.ties.extract.amend that return FeatureVector
 FeatureVector ContextDetails.getContext()
          Returns a feature vector representing the context of the token.
 

Constructors in de.fu_berlin.ties.extract.amend with parameters of type FeatureVector
ContextDetails(String theToken, int tokenRep, int tokenIndex, boolean wsBefore, FeatureVector features)
          Creates a new instance.
ContextDetails(TokenDetails orgDetails, FeatureVector features)
          Creates a new instance, re-using field values from a TokenDetails instance.
TrainingContextDetails(String theToken, int tokenRep, int tokenIndex, boolean wsBefore, FeatureVector features, CombinationState predicted, CombinationState expected)
          Creates a new instance.
TrainingContextDetails(TokenDetails orgDetails, FeatureVector features, CombinationState predicted, CombinationState expected)
          Creates a new instance, re-using field values from a TokenDetails instance.
 

Uses of FeatureVector in de.fu_berlin.ties.filter
 

Methods in de.fu_berlin.ties.filter that return FeatureVector
 FeatureVector RepresentationFilter.buildFeatures(Element element)
          Converts an element into a feature vector to be used by the trainable classifier.
abstract  FeatureVector TrainableFilter.buildFeatures(Element element)
          Converts an element into a feature vector to be used by the trainable classifier.
 



Copyright © 2003-2004 Christian Siefkes. All Rights Reserved.