方法证据记录
Specificity
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Specificity (True Negative Rate)
分类方法记录 · 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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