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Balanced Accuracy/Evidence
Method evidence record

Balanced Accuracy

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.

Sources recorded, not reviewed

Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Balanced Classification Accuracy
Taxonomic method record · mcdm / model-evaluation
  • 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 10.1109/ICPR.2010.764
  • Powers, D. M. (2011). Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies, 2(1), 37-63. · URL
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

No curated claims yet

This view does not invent a claim assessment when the ledger has none.

Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketAccuracymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketF1-Scoremachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMatthews Correlation Coefficientmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRecall (Sensitivity)machine-suggested · Relational suggestion, not evidence.Taxonomic bucketSpecificitymachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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