An Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition

نویسندگان
Cudney, Elizabeth A. ID 1
Ragsdell, Kenneth M. ID 2
Taguchi, Genichi ID 3
Hong, Jungeui ID 4
Jugulum, Rajesh ID 5
Paryani, Kioumars ID 6

1 University of Missouri – Rolla, Rolla, Missouri 65409 USA

2 University of Missouri – Rolla, Rolla, Missouri 65409 USA

3 Ohken Associates, Tokyo, Japan

4 Chungju National University, Chungju, 380-702 South Korea

5 Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 U.S.A.

6 Lawrence Technological University, Southfield, Michigan, U.S.A.

doi
چکیده

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.

کلیدواژه‌ها
Mahalanobis-Taguchi System, Mahalanobis distance, Neural Network, Pattern recognition, Orthogonal array, Signal-to-noise ratio, Mahalanobis space (reference group)