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http://dx.doi.org/10.7465/jkdi.2015.26.1.255

Two optimal threshold criteria for ROC analysis  

Cho, Min Ho (Department of Statistics, Sungkyunkwan University)
Hong, Chong Sun (Department of Statistics, Sungkyunkwan University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.1, 2015 , pp. 255-260 More about this Journal
Abstract
Among many optimal threshold criteria from ROC curve, the closest-to-(0,1) and amended closest-to-(0,1) criteria are considered. An ROC curve that passes close to the (0,1) point indicates that two models are well classified. In this case, the ROC curve is located far from the (1,0) point. Hence we propose two criteria: the farthest-to-(1,0) and amended farthest-to-(1,0) criteria. These criteria are found to have a relationship with the KolmogorovSmirnov statistic as well as some optimal threshold criteria. Moreover, we derive that a definition for the proposed criteria with more than two dimensions and with relations to multi-dimensional optimal threshold criteria.
Keywords
ROC; threshold; true negative rate; true positive rate;
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Times Cited By KSCI : 5  (Citation Analysis)
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