期刊
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
卷 49, 期 9, 页码 2080-2093出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/03610926.2019.1568485
关键词
confusion matrix; sensitivity; specificity; ROC; KS; false positive; false negative; true positive; true negative
Confusion Matrix is an important measure to evaluate the accuracy of credit scoring models. However, the literature about Confusion Matrix is limited. The analytical properties of Confusion Matrix are ignored. Moreover, the concept of Confusion Matrix is confusing. In this article, we systematically study Confusion Matrix and its analytical properties. We enumerate 16 possible variants of Confusion Matrix and show that only 8 are reasonable. We study the relationship between Confusion Matrix and 2 other performance measures: the receiver operating characteristic curve (ROC) and Kolmogorov-Smirnov statistic (KS). We show that an optimal cutoff score can be attained by KS.
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