Swarm BIAS-variance analysis of an evolutionary neural network classifier

Emilio Miguelanez, A. M S Zalzala

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the search of a system satisfying all the requirements of an automated classifier, evolutionary artificial neural networks have been successfully applied to a number of problems, in particular to problems where there is not a deep knowledge of the phenomena and other methods tend to fail. There are many neural models that efficiently solve either function approximation problems in general terms or some particular problems like classification, pattern recognition, clustering and time-series prediction. This success is due to these models main characteristics, in particular those matching the essentials for an automated classifier: keeping bias and variance low. This paper presents a classifier system based on the benefits arising from the interaction between evolutionary algorithms, such as particle swarm optimization, and artificial neural networks. And a bias variance decomposition of the predictive error shows that the success of the proposed approach lies in the ability of the learning algorithm to properly tune the bias/variance trade-off to reduce the prediction error. To measure the performance, the purposed classifier will be tested on three different well known benchmark problems: the Fisher Iris data set, the Australian credit card assessment and the Pima diabetes data set.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2006
Subtitle of host publicationIASTED International Conference on Artificial Intelligence and Applications, AIA 2006; Innsbruck; Austria; 13 February 2006 through 16 February 2006
Pages256-261
Number of pages6
Publication statusPublished - 2006
EventIASTED International Conference on Artificial Intelligence and Applications - Innsbruck, Austria
Duration: 13 Feb 200616 Feb 2006

Conference

ConferenceIASTED International Conference on Artificial Intelligence and Applications
Abbreviated titleAIA 2006
CountryAustria
CityInnsbruck
Period13/02/0616/02/06

Keywords

  • Artificial neural networks (ANNs)
  • Bias variance trade-off
  • Particle swarm optimization (PSO)

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    Miguelanez, E., & Zalzala, A. M. S. (2006). Swarm BIAS-variance analysis of an evolutionary neural network classifier. In Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2006: IASTED International Conference on Artificial Intelligence and Applications, AIA 2006; Innsbruck; Austria; 13 February 2006 through 16 February 2006 (pp. 256-261)