A notable swarm approach to evolve neural network for classification in data mining

Satchidananda Dehuri, Bijan Bihari Mishra, Sung Bae Cho

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

Abstract

This paper presents a novel and notable swarm approach to evolve an optimal set of weights and architecture of a neural network for classification in data mining. In a distributed environment the proposed approach generates randomly multiple architectures competing with each other while fine-tuning their architectural loopholes to generate an optimum model with maximum classification accuracy. Aiming at better generalization ability, we analyze the use of particle swarm optimization (PSO) to evolve an optimal architecture with high classification accuracy. Experiments performed on benchmark datasets show that the performance of the proposed approach has good classification accuracy and generalization ability. Further, a comparative performance of the proposed model with other competing models is given to show its effectiveness in terms of classification accuracy.

Original languageEnglish
Title of host publicationAdvances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers
Pages1121-1128
Number of pages8
EditionPART 1
DOIs
Publication statusPublished - 2009
Event15th International Conference on Neuro-Information Processing, ICONIP 2008 - Auckland, New Zealand
Duration: 2008 Nov 252008 Nov 28

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5506 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Neuro-Information Processing, ICONIP 2008
Country/TerritoryNew Zealand
CityAuckland
Period08/11/2508/11/28

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint

Dive into the research topics of 'A notable swarm approach to evolve neural network for classification in data mining'. Together they form a unique fingerprint.

Cite this