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

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.

Meeting Name

ASME 2005 International Mechanical Engineering Congress and Exposition (2005: Nov. 5-11, Orlando, FL)

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Mahalanobis-Taguchi System; Neural Networks

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2005 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

11 Nov 2005

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