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Accuracy/Evidence
Method evidence record

Accuracy

Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class.

Sources recorded, not reviewed

Source record

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

Classification Accuracy
Taxonomic method record · mcdm / model-evaluation
  • Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. · DOI 10.1016/j.patrec.2005.10.010
  • 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 bucketBalanced Accuracymachine-suggested · Relational suggestion, not evidence.Same method familyConfusion Matrixmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketF1-Scoremachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPrecisionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRecall (Sensitivity)machine-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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