The use of confidence measures to enhance combination strategies in multi-network neuro-fuzzy systems

Canuto, A. and Howells, G. and Fairhurst, M.C. (2000) The use of confidence measures to enhance combination strategies in multi-network neuro-fuzzy systems. Connection Science, 12 (3-4). pp. 315-331. ISSN 0954-0091. (The full text of this publication is not available from this repository)

The full text of this publication is not available from this repository. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1080/09540090010014089

Abstract

It is well known that substantial improvements can be obtained in difficult pattern recognition problems by combining or integrating the outputs of multiple neural classifiers. This paper analyses the performance of some combination schemes applied to a multi-hybrid neural system which is composed of neural and fuzzy neural networks. Essentially, the combination methods employ different ways to extract valuable information from the output of the experts through the use of confidence (weights) measures of the ensemble members to each class. An empirical evaluation in a handwritten numeral. recognition task is used to investigate the performance of the presented methods in comparison with some existing combination methods.

Item Type: Article
Uncontrolled keywords: multi-network neuro-fuzzy systems; neural networks; fuzzy neural networks; confidence measures
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Faculties > Science Technology and Medical Studies > School of Computing
Depositing User: P. Ogbuji
Date Deposited: 09 Apr 2009 12:06
Last Modified: 29 May 2012 09:05
Resource URI: http://kar.kent.ac.uk/id/eprint/16212 (The current URI for this page, for reference purposes)
  • Depositors only (login required):