지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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A receiver operating characteristic (ROC) curve plots the true positive rate of a classifier against its false positive rate, both of which are accuracy measures of the classifier. The ROC curve has several interesting geometrical properties, including concavity which is a necessary condition for a classifier to be optimal. In this paper, we study the nonparametric maximum likelihood estimator (NPMLE) of a concave ROC curve and its modification to reduce bias. We characterize the NPMLE as a solution to a geometric programming,a special type of a mathematical optimization problem. We find that the NPMLE is close to the convex hull of the empirical ROC curve and,thus, has smaller variance but positive bias at a given false positive rate.
To reduce the bias, we propose a modification of the NPMLE which minimizes the L_1 distance from the empirical ROC curve. We numerically compare the finite sample performance of three estimators, the empirical ROC curve, the NMPLE, and the modified NPMLE. Finally, we apply the estimators to estimating the optimal ROC curve of the variance-threshold classifier to segment a low depth of field image and to finding a diagnostic tool with multiple tests for detection of hemophilia A carrier.
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참고문헌 (25)
참고문헌 신청
A. Mutapcic / / ggplab: A Matlab toolbox for geometric programming
C. E. Metz / 1999 / "Proper" binormal ROC curves: theory and maximum-likelihood estimation / J. Math. Psych 43 (1) : 1 ~ 33
C. Feltz / 1985 / Maximum likelihood estimation of the survival functions of N stochastically ordered random variables / J. Amer. Statist. Assoc 80 (392) : 1012 ~ 1019
C. Llyod / 2000 / Regression models for convex ROC curves / Biometrics 56 : 862 ~ 867
C. Llyod / 2002 / Estimation of a convex ROC curve / Statist. Probab. Lett 59 (1) : 99 ~ 111
C. E. Metz / 1999 / "Proper" binormal ROC curves: theory and maximum-likelihood estimation / J. Math. Psych 43 (1) : 1 ~ 33
C. Feltz / 1985 / Maximum likelihood estimation of the survival functions of N stochastically ordered random variables / J. Amer. Statist. Assoc 80 (392) : 1012 ~ 1019
C. Llyod / 2000 / Regression models for convex ROC curves / Biometrics 56 : 862 ~ 867
C. Llyod / 2002 / Estimation of a convex ROC curve / Statist. Probab. Lett 59 (1) : 99 ~ 111
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