A Comparison Study of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition
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.
J. Hong et al., "A Comparison Study of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition," 2005 ASME International Mechanical Engineering Congress and Exposition, American Society of Mechanical Engineers (ASME), Nov 2005.
Engineering Management and Systems Engineering
Keywords and Phrases
Mahalanobis-Taguchi System; Neural Networks
Article - Conference proceedings
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