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.

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.


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