Package opennlp.tools.util.eval
Class FMeasure
java.lang.Object
opennlp.tools.util.eval.FMeasure
The
FMeasure is a utility class for evaluators
which measures precision, recall and the resulting f-measure.
Evaluation results are the arithmetic mean of the precision scores calculated for each reference sample and the arithmetic mean of the recall scores calculated for each reference sample.
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptiondoublef-measure = 2 * precision * recall / (precision + recall).doubledoublevoidMerge results intometric.static doubleCalculates the precision score for the given reference and predicted spans.static doubleCalculates the recall score for the given reference and predicted spans.toString()voidupdateScores(Object[] references, Object[] predictions) Updates the score based on the number of true positives and the number of predictions and references.
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Constructor Details
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FMeasure
public FMeasure()
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Method Details
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getPrecisionScore
public double getPrecisionScore()- Returns:
- Retrieves the arithmetic mean of the precision scores calculated for each evaluated sample.
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getRecallScore
public double getRecallScore()- Returns:
- Retrieves the arithmetic mean of the recall score calculated for each evaluated sample.
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getFMeasure
public double getFMeasure()f-measure = 2 * precision * recall / (precision + recall).- Returns:
- Retrieves the f-measure or
-1if precision + recall<= 0
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updateScores
Updates the score based on the number of true positives and the number of predictions and references.- Parameters:
references- the provided referencespredictions- the predicted spans
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mergeInto
Merge results intometric.- Parameters:
measure- TheFMeasureto merge.
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toString
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precision
Calculates the precision score for the given reference and predicted spans.- Parameters:
references- The gold standard spans.predictions- The predicted spans.- Returns:
- The precision score or
NaNif there are no predicted spans.
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recall
Calculates the recall score for the given reference and predicted spans.- Parameters:
references- The gold standard spanspredictions- The predicted spans- Returns:
- The recall score or
NaNif there are no reference spans.
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