double |
Accuracy.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the accuracy of the machine learning predictions compared to a gold standard
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abstract double |
APRF.calculate(AMapping predictions,
GoldStandard goldStandard) |
The Abstract method to be implemented for calculating the accuracy of the machine learning predictions compared to a gold standard
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abstract double |
APseudoPRF.calculate(AMapping predictions,
GoldStandard goldStandard) |
The Abstract method to be implemented for calculating the accuracy of the machine learning predictions compared to a gold standard
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double |
AUC.calculate(AMapping predictions,
GoldStandard goldStandard) |
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double |
FMeasure.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the F-Measure of the machine learning predictions compared to a gold standard
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double |
FMeasure.calculate(AMapping predictions,
GoldStandard goldStandard,
double beta) |
The method calculates the F-Measure of the machine learning predictions compared to a gold standard
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double |
IQualitativeMeasure.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method to be implemented for calculating the accuracy of the machine learning predictions compared to a gold standard
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double |
Precision.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the precision of the machine learning predictions compared to a gold standard
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double |
PseudoFMeasure.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo F-Measure of the machine learning predictions compared to a gold standard for beta = 1 .
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double |
PseudoFMeasure.calculate(AMapping predictions,
GoldStandard goldStandard,
double beta) |
The method calculates the pseudo F-Measure of the machine learning predictions compared to a gold standard for different beta values
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double |
PseudoPrecision.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo precision of the machine learning predictions compared to a gold standard , which is basically how well the mapping
maps one single s to one single t.
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double |
PseudoRecall.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo recall of the machine learning predictions compared to a gold standard , which is how many of the s and t
were mapped.
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double |
PseudoRefPrecision.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo reference Precision of the machine learning predictions compared to a gold standard for beta = 1 .
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double |
PseudoRefRecall.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo reference Recall of the machine learning predictions compared to a gold standard for beta = 1 .
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double |
Recall.calculate(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the recall of the machine learning predictions compared to a gold standard
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Map<EvaluatorType,Double> |
QualitativeMeasuresEvaluator.evaluate(AMapping predictions,
GoldStandard goldStandard,
Set<EvaluatorType> evaluationMeasures) |
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double |
FMeasure.precision(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the precision of the machine learning predictions compared to a gold standard
|
double |
PseudoFMeasure.precision(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo precision of the machine learning predictions compared to a gold standard
|
double |
PseudoRefFMeasure.precision(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo reference precision of the machine learning predictions compared to a gold standard
|
double |
FMeasure.recall(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the recall of the machine learning predictions compared to a gold standard
|
double |
PseudoFMeasure.recall(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo recall of the machine learning predictions compared to a gold standard
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double |
PseudoRefFMeasure.recall(AMapping predictions,
GoldStandard goldStandard) |
The method calculates the pseudo reference recall of the machine learning predictions compared to a gold standard
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static double |
APRF.trueNegative(AMapping predictions,
GoldStandard goldStandard) |
|