MCDMClassification Metric

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.

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Sources

  1. Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI: 10.1016/j.patrec.2005.10.010
  2. 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. DOI: 10.9735/2229-3981

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Referenced by

ScholarGateAccuracy (Classification Accuracy). Retrieved 2026-06-04 from https://scholargate.app/en/model-evaluation/accuracy