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

Packages that use Feature
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). 
 

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

Subclasses of Feature in de.fu_berlin.ties.classify.feature
 class DefaultFeature
          Default implementation of the Feature class.
 

Methods in de.fu_berlin.ties.classify.feature that return types with arguments of type Feature
protected  Collection<Feature> FeatureSet.store()
          Returns the collection used for storing the features.
protected  Collection<Feature> DefaultFeatureVector.store()
          Returns the collection used for storing the features.
protected abstract  Collection<Feature> FeatureVector.store()
          Returns the collection used for storing the features.
 

Methods in de.fu_berlin.ties.classify.feature with parameters of type Feature
 void FeatureVector.add(Feature feature)
          Adds a feature to this vector.
 

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

Methods in de.fu_berlin.ties.classify.winnow with parameters of type Feature
protected  void Winnow.adjustWeights(Feature feature, short[] directions)
          Adjusts the weights of a feature for all classes.
 float[] SharedWinnowStore.getWeights(Feature feature)
          Returns the weights of a feature.
abstract  float[] WinnowStore.getWeights(Feature feature)
          Returns the weights of a feature.
 float[] DefaultWinnowStore.getWeights(Feature feature)
          Returns the weights of a feature.
 boolean WinnowStore.isRelevant(Feature feature)
          Whether a feature is considered relevant for classification.
 void SharedWinnowStore.putWeights(Feature feature, float[] weights)
          Stores new weights for a feature.
abstract  void WinnowStore.putWeights(Feature feature, float[] weights)
          Stores new weights for a feature.
 void DefaultWinnowStore.putWeights(Feature feature, float[] weights)
          Stores new weights for a feature.
 void WinnowStore.setRelevant(Feature feature, boolean relevant)
          Marks a feature as relevant or irrelevant for classification.
protected  void Winnow.updateScores(Feature feature, float[] scores)
          Updates the score (activation values) for all classes by adding the weights of a feature.
 

Uses of Feature in de.fu_berlin.ties.context
 

Subclasses of Feature in de.fu_berlin.ties.context
 class GlobalFeature
          An immutable representation of a feature that can be used for classification.
 class LocalFeature
          An immutable representation of the local part of a feature, useful to cache and re-use the parts of feature representation that do not depend on the relative position of the element to classify.
 

Methods in de.fu_berlin.ties.context that return types with arguments of type Feature
protected  List<Feature> DefaultRepresentation.buildPrior(PriorRecognitions priorRecognitions)
          Builds the pseudo-axis of prior recognitions.
protected  List<Feature> DefaultRepresentation.filterRepresentation(FeatureVector originalRep)
          Creates a filtered view of a context representation.
 LinkedList<Feature> PriorRecognitions.Pair.getCachedFeatures()
          Returns the list of features representing the recognition, initially null.
 

Method parameters in de.fu_berlin.ties.context with type arguments of type Feature
protected  void DefaultRepresentation.buildFeatures(String axisName, Element element, ElementPosition position, boolean recurseInsteadOfText, LinkedList<Feature> featureList, boolean addAtEnd, Map<Element,List<LocalFeature>> cache)
          Builds the features of an element and appends them to the specified featureList.
protected  void DefaultRepresentation.buildTextFeatures(String axisName, Element element, String trimmedLeft, String trimmedMain, String trimmedRight, LinkedList<Feature> featureList)
          Builds the context representation of text in an element, differentiating between three kinds of textual contents: a left part, a main part, and a right part.
static void GlobalFeature.globalize(String axisName, Iterator<LocalFeature> localIter, LinkedList<Feature> globalFeatures, boolean addAtEnd)
          Converts a series of LocalFeatures into global features, adding the created global features to a linked list.
protected  void DefaultRepresentation.handleAncestors(Element element, int ancestorsToAdd, int ancestorSiblingsToAdd, LinkedList<Feature> ancestorFeatures, LinkedList<Feature> ancestorSiblingFeatures, Bag processedAncestorNames, Map<Element,List<LocalFeature>> cache)
          Handles ancestors and ancestor siblings of an element.
protected  void DefaultRepresentation.handleAncestors(Element element, int ancestorsToAdd, int ancestorSiblingsToAdd, LinkedList<Feature> ancestorFeatures, LinkedList<Feature> ancestorSiblingFeatures, Bag processedAncestorNames, Map<Element,List<LocalFeature>> cache)
          Handles ancestors and ancestor siblings of an element.
protected  ElementPosition DefaultRepresentation.handleSiblings(String axisPrefix, Element element, int baseNumber, LinkedList<Feature> precedingFeatures, LinkedList<Feature> followingFeatures, Map<Element,List<LocalFeature>> cache)
          Adds the preceding and following siblings of an element.
protected  ElementPosition DefaultRepresentation.handleSiblings(String axisPrefix, Element element, int baseNumber, LinkedList<Feature> precedingFeatures, LinkedList<Feature> followingFeatures, Map<Element,List<LocalFeature>> cache)
          Adds the preceding and following siblings of an element.
 void PriorRecognitions.Pair.setCachedFeatures(LinkedList<Feature> features)
          Sets the list of features representing the recognition.
 



Copyright © 2003-2007 Christian Siefkes. All Rights Reserved.