A likelihood-MPEC approach to target classification |
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Authors: | Tim Olson Jong-Shi Pang Carey Priebe |
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Institution: | (1) Department of Mathematics, University of Florida, Gainesville, Florida 32611-8105, USA, e-mail: olson@math.ufl.edu, US;(2) Department of Mathematical Sciences, Whiting School of Engineering, The Johns Hopkins University, Baltimore, Maryland 21218-2682, USA, e-mail: pang@mts.jhu.edu, cep@jhu.edu, US |
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Abstract: | In this paper we develop a method for classifying an unknown data vector as belonging to one of several classes. This method
is based on the statistical methods of maximum likehood and borrowed strength estimation. We develop an MPEC procedure (for
Mathematical Program with Equilibrium Constraints) for the classification of a multi-dimensional observation, using a finite
set of observed training data as the inputs to a bilevel optimization problem. We present a penalty interior point method
for solving the resulting MPEC and report numerical results for a multispectral minefield classification application. Related
approaches based on conventional maximum likehood estimation and a bivariate normal mixture model, as well as alternative
surrogate classification objective functions, are described.
Received: October 26, 1998 / Accepted: June 11, 2001?Published online March 24, 2003
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ID="***"The authors of this work were all partially supported by the Wright Patterson Air Force Base via Veda Contract F33615-94-D-1400.
The first and third author were also supported by the National Science Foundation under grant DMS-9705220.
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ID="*"The work of this author was based on research supported by the U.S. National Science Foundation under grant CCR-9624018.
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ID="**"The work of this author was supported by the Office of Naval Research under grant N00014-95-1-0777. |
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Keywords: | Mathematics Subject Classification (2000): 62G07 62P30 90C26 90C30 90C33 90C90 |
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