TY - JOUR ID - 3924 TI - An Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition JO - Journal of Industrial and Systems Engineering JA - JISE LA - en SN - 1735-8272 AU - Cudney, Elizabeth A. AU - Hong, Jungeui AU - Jugulum, Rajesh AU - Paryani, Kioumars AU - Ragsdell, Kenneth M. AU - Taguchi, Genichi AD - University of Missouri – Rolla, Rolla, Missouri 65409 U.S.A. AD - Chungju National University, Chungju, 380-702 South Korea AD - Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 U.S.A. AD - Lawrence Technological University, Southfield, Michigan, U.S.A. AD - Ohken Associates, Tokyo, Japan Y1 - 2007 PY - 2007 VL - 1 IS - 2 SP - 139 EP - 150 KW - Mahalanobis-Taguchi System KW - Mahalanobis distance KW - Neural Network KW - Pattern recognition KW - Orthogonal array KW - Signal-to-noise ratio KW - Mahalanobis space (reference group) DO - N2 - 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. UR - https://www.jise.ir/article_3924.html L1 - https://www.jise.ir/article_3924_5f31f4ac2ae98ac31c98b527e637819e.pdf ER -