Uses of Package
de.fu_berlin.ties.eval

Packages that use de.fu_berlin.ties.eval
de.fu_berlin.ties.classify This package provides functionality for classification of texts and feature vectors. 
de.fu_berlin.ties.classify.winnow This package contains the Winnow classification algorithm and related algorithms and classes. 
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 entity recognition. 
de.fu_berlin.ties.filter This packages provides generic filtering and rewriting functionality. 
 

Classes in de.fu_berlin.ties.eval used by de.fu_berlin.ties.classify
EvalStatus
          Type-safe enumeration of possible evaluation states for predictions (unknown, correct, spurious etc.) and answer keys (missing etc.).
 

Classes in de.fu_berlin.ties.eval used by de.fu_berlin.ties.classify.winnow
EvalStatus
          Type-safe enumeration of possible evaluation states for predictions (unknown, correct, spurious etc.) and answer keys (missing etc.).
 

Classes in de.fu_berlin.ties.eval used by de.fu_berlin.ties.eval
AccuracyView
          Provides a read-only view on Accuracy statistics and the underlying raw counts.
EvalInput
          Classes implementing this interface provide input for calculating evaluation metrics: true positives, false negatives and false positives.
EvalStatus
          Type-safe enumeration of possible evaluation states for predictions (unknown, correct, spurious etc.) and answer keys (missing etc.).
FeatureCountView
          Provides a read-only view on the statistics calculated by the FeatureCount class and the underlying raw counts.
FMetrics
          This class manages and updates evaluation results, calculating precision (P), recall (R) and F-measure (F).
FMetricsSummary
          Implementations of this interface can show statistical summaries of precision, recall, and F1 metrics updated in several operations.
FMetricsView
          A read-only view of the evaluation results calculated by the FMetrics class and the underlying raw counts.
Mistake
          Each instance of this class describe a mistake.
Mistake.MistakeTypes
          The types of mistakes that can occur.
MistakeMatrix
          Stores the results of a mistake analysis performed by MistakeAnalyzer.
MultiFMetricsView
          A read-only view of multiple FMetrics and the sums and averages calculated over them.
 

Classes in de.fu_berlin.ties.eval used by de.fu_berlin.ties.extract
Accuracy
          Counts true and false items and measures the accuracy: A = true / (true + false).
AccuracyView
          Provides a read-only view on Accuracy statistics and the underlying raw counts.
EvalStatus
          Type-safe enumeration of possible evaluation states for predictions (unknown, correct, spurious etc.) and answer keys (missing etc.).
FMetricsView
          A read-only view of the evaluation results calculated by the FMetrics class and the underlying raw counts.
MultiFMetricsView
          A read-only view of multiple FMetrics and the sums and averages calculated over them.
 

Classes in de.fu_berlin.ties.eval used by de.fu_berlin.ties.filter
FMetricsView
          A read-only view of the evaluation results calculated by the FMetrics class and the underlying raw counts.
 



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