Date of Award
3-1997
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Steven K. Rogers, PhD
Abstract
The general pattern recognition problem always involves the extraction of features to be used in pattern classification. There are no theoretical limitations to the number of features which can be obtained for a given pattern recognition problem. This research will develop a correlation procedure for screening a large feature set without the use of a trained classifier. The results will be compared to established saliency metrics such as the Fisher ratio and derivative-based techniques such as Ruck's saliency.
AFIT Designator
AFIT-GOR-ENG-97M-04
DTIC Accession Number
ADA323712
Recommended Citation
Gregg, Daniel W., "Decision Boundary Analysis Feature Selection for Breast Cancer Diagnosis" (1997). Theses and Dissertations. 5963.
https://scholar.afit.edu/etd/5963