Abstract
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.
Recommended Citation
J. Hong et al., "An Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition," Inderscience, Jan 2007.
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Mahalanobis Distance; Mahalanobis-Taguchi System; Neural Network; Pattern Recognition
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2007 Inderscience, All rights reserved.
Publication Date
01 Jan 2007
