Date of Award

9-2008

Document Type

Thesis

Degree Name

Master of Science in Applied Mathematics

Department

Department of Mathematics and Statistics

First Advisor

Mark E. Oxley, PhD

Abstract

The need for optimal target detection arises in many different fields. Due to the complexity of many targets, it is thought that the combination of multiple classification systems, which can be tuned to several individual target attributes or features, might lead to more optimal target detection performance. The ROC curves of fused independent two-label classification systems may be generated by the mathematical combination of their ROC curves to achieve optimal classifier performance without the need to test every Boolean combination. The monotonic combination of two-label independent classification systems which assign labels to the same target types results in a lattice of ROC curves which are epimorphic to the corresponding combinations of classification systems. Provided the ROC curves of individual systems are available, testing the lattice of ROC curves in software with existing individual ROC curves can represent a significant cost savings in the design of optimal classification systems.

AFIT Designator

AFIT-GAM-ENC-08-06

DTIC Accession Number

ADA486884

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