Browse > Article
http://dx.doi.org/10.5351/CKSS.2012.19.4.629

Bivariate ROC Curve and Optimal Classification Function  

Hong, C.S. (Department of Statistics, Sungkyunkwan University)
Jeong, J.A. (Research Institute of Applied Statistics, Sungkyunkwan University)
Publication Information
Communications for Statistical Applications and Methods / v.19, no.4, 2012 , pp. 629-638 More about this Journal
Abstract
We propose some methods to obtain optimal thresholds and classification functions by using various cutoff criterion based on the bivariate ROC curve that represents bivariate cumulative distribution functions. The false positive rate and false negative rate are calculated with these classification functions for bivariate normal distributions.
Keywords
Credit evaluation; default; classification; cutoff criteria; misclassification rate;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Hong, C. S. and Joo, J. S. (2010). Optimal thresholds from non-normal mixture, The Korean Journal of Applied Statistics, 23, 943-953.   과학기술학회마을   DOI   ScienceOn
2 Hong, C. S., Kim, G. C. and Jeong, J. A. (2012). Bivariate ROC curve, The Korean Journal of Applied Statistics, 19, 277-286.   과학기술학회마을   DOI   ScienceOn
3 Krzanowski, W. J. and Hand, D. J. (2009). ROC Curves for Continuous Data, Chapman & Hall/CRC, Monographs on Statistics & Applied Probability, 111, Florida.
4 Lambert, J. and Lipkovich, I. (2008). A macro for getting more out of your ROC curve, SAS Global Forum, 231.
5 Perkins, N. J. and Schisterman, E. F. (2006). The inconsistency of "Optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve, American Journal of Epidemiology, 163, 670-675.   DOI   ScienceOn
6 Youden, W. J. (1950). Index for rating diagnostic test, Cancer, 3, 32-35.   DOI
7 Connell, F. A. and Koepsell, T. D. (1985). Measures of gain in certainty from a diagnostic test, American Journal of Epidemiology, 121, 744-753.   DOI   ScienceOn