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Proceedings Paper

Confidence of a ROC manifold
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Paper Abstract

A Classification system such as an Automatic Target Recognition (ATR) system with N possible output labels (or decisions) will have N(N-1) possible errors. The Receiver Operating Characteristic (ROC) manifold was created to quantify all of these errors. Finite truth data will produce an approximation to a ROC manifold. How well does the approximate ROC manifold approximate the TRUE ROC manifold? Several metrics exist that quantify the approximation ability, but researchers really wish to quantify the confidence in the approximate ROC manifold. This paper will review different confidence definitions for ROC curves and will derive an expression for confidence of a ROC manifold. The foundation of the confidence expression is based upon the Chebychev inequality..

Paper Details

Date Published: 27 April 2010
PDF: 12 pages
Proc. SPIE 7697, Signal Processing, Sensor Fusion, and Target Recognition XIX, 76970T (27 April 2010); doi: 10.1117/12.850892
Show Author Affiliations
Mark E. Oxley, Air Force Institute of Technology (United States)
Christine M. Schubert, Virginia Commonwealth Univ. (United States)
Steven N. Thorsen, U.S. Air Force Academy (United States)


Published in SPIE Proceedings Vol. 7697:
Signal Processing, Sensor Fusion, and Target Recognition XIX
Ivan Kadar, Editor(s)

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