Classification rule induction based on relevant, irredundant attributes and rule expansion

George Lashkia*, Laurence Anthony, Hiroyasu Koshimizu

*この研究の対応する著者

研究成果: Conference contribution

抄録

In this paper we focus on the induction of classification rules from examples. Conventional algorithms fail in discovering effective knowledge when the database contains irrelevant information. We present a new rule extraction method, RGT, which tackles this problem by employing only relevant and irredundant attributes. Simplicity of rules is also our major concern. In order to create only simple rules, we estimate the purity of patterns and propose a rule merging and expending procedures. In this paper, we describe the methodology for the RGT algorithm, discuss its properties, and compare it with conventional methods.

本文言語English
ホスト出版物のタイトルWMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
ページ191-196
ページ数6
出版ステータスPublished - 2005 12 1
イベント9th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2005 - Orlando, FL, United States
継続期間: 2005 7 102005 7 13

出版物シリーズ

名前WMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
8

Conference

Conference9th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2005
国/地域United States
CityOrlando, FL
Period05/7/1005/7/13

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • 情報システム

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