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混同行列×特異度(Specificity)×
分野モデル評価モデル評価
系統MCDMMCDM
提唱年20th century20th century
提唱者Statistical foundationsHistorical statistical foundations
種類Evaluation visualizationEvaluation metric
原典Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
別名Error Matrix, Contingency TableTrue Negative Rate, TNR
関連55
概要The confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics.Specificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are costly.
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ScholarGate手法を比較: Confusion Matrix · Specificity. 2026-06-17に以下より取得 https://scholargate.app/ja/compare