Exploring comprehensible classification rules from trained neural networks integrated with a time-varying binary particle swarm optimizer


ÖZBAKIR L., Delice Y.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol.24, no.3, pp.491-500, 2011 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 3
  • Publication Date: 2011
  • Doi Number: 10.1016/j.engappai.2010.11.008
  • Title of Journal : ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
  • Page Numbers: pp.491-500

Abstract

Purpose: Extracting comprehensible classification rules is the most emphasized concept in data mining researches. In order to obtain accurate and comprehensible classification rules from databases, a new approach is proposed by combining advantages of artificial neural networks (ANN) and swarm intelligence.