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Recall (Sensitivität)×Balanced Accuracy×
FachgebietModellevaluationModellevaluation
FamilieMCDMMCDM
Entstehungsjahr20th century2010
UrheberHistorical statistical foundationsBrodersen, Ong, Stephan, and Buhmann
TypEvaluation metricEvaluation metric
Wegweisende QuelleFawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010). The balanced accuracy and its posterior distribution. 20th International Conference on Pattern Recognition (ICPR), 3121-3124. DOI ↗
AliasnamenSensitivity, True Positive Rate, TPRAverage Recall, Equal-weight Average Sensitivity
Verwandt55
ZusammenfassungRecall measures the proportion of actual positive cases that were correctly identified by the classifier. It answers the question: 'Of all the cases that were truly positive, how many did we find?' Recall is critical in scenarios where missing positive cases is costly.Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regardless of class frequency in the dataset.
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ScholarGateMethoden vergleichen: Recall (Sensitivity) · Balanced Accuracy. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare