Determination of the Mahalanobis Matrix using Nonparametric Noise Estimations

Author

Amaury Lendasse, Missouri University of Science and TechnologyFollow
F. Corona
J. Hao
N. Reyhani
M. Verleysen

Abstract

In This Paper, the Problem of an Optimal Transformation of the Input Space for Function Approximation Problems is Addressed. the Transformation is Defined Determining the Mahalanobis Matrix that Minimizes the Variance of Noise. to Compute Variance of the Noise, a Nonparametric Estimator Called the Delta Test Paradigm is Used. the Proposed Approach is Illlustrated on Two Different Benchmarks.

Recommended Citation

A. Lendasse et al., "Determination of the Mahalanobis Matrix using Nonparametric Noise Estimations," ESANN 2006 Proceedings - European Symposium on Artificial Neural Networks, pp. 227 - 232, European Symposium on Artificial Neural Networks, Jan 2006.

Department(s)

Engineering Management and Systems Engineering

Comments

Academy of Finland, Grant 44886

International Standard Book Number (ISBN)

978-293030706-0

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 European Symposium on Artificial Neural Networks, All rights reserved.

Publication Date

01 Jan 2006