Title

Levenberg-Marquardt and Conjugate Gradient Methods Applied to a High-order Neural Network

Abstract

The HONEST network is a high order neural network that uses product units and adaptable exponential weights. In this paper, we explore the use of several learning methods with the HONEST network: Levenberg-Marquardt (LM), Conjugate Gradient (CG), Scaled Conjugate Gradient (a technique that combines LM and CG), and resilient propagation (RP). Using a benchmark of 19 datasets, we find that the first three methods mentioned produce lower average test set errors than RP to a statistically significant extent.

Meeting Name

2013 International Joint Conference on Neural Networks (IJCNN) (2013: Aug. 4-9, Dallas, TX)

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

9781467361293; 9781467361286

International Standard Serial Number (ISSN)

2161-4393

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2013 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.


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