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A Comparison Study of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition

[+] Author Affiliations
Jungeui Hong

Chungju National University

Elizabeth A. Cudney, Kenneth M. Ragsdell

University of Missouri at Rolla

Genichi Taguchi

Ohken Associates

Rajesh Jugulum

Massachusetts Institute of Technology

Kioumars Paryani

General Motors Corporation

Paper No. IMECE2005-80029, pp. 109-115; 7 pages
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Design Engineering, Parts A and B
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Design Engineering Division
  • ISBN: 0-7918-4215-0 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME


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.

Copyright © 2005 by ASME



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