Mining association rules from databases with continuous attributes using genetic network programming

Karla Taboada*, Eloy Gonzales, Kaoru Shimada, Shingo Mabu, Kotaro Hirasawa, Jinglu Hu

*この研究の対応する著者

研究成果: Conference contribution

抄録

Most association rule mining algorithms make use of discretization algorithms for handling continuous attributes. Discretization is a process of transforming a continuous attribute value into a finite number of intervals and assigning each interval to a discrete numerical value. However, by means of methods of discretization, it is difficult to get highest attribute interdependency and at the same time to get lowest number of intervals. In this paper we present an association rule mining algorithm that is suited for continuous valued attributes commonly found in scientific and statistical databases. We propose a method using a new graph-based evolutionary algorithm named "Genetic Network Programming (GNP)" that can deal with continues values directly, that is, without using any discretization method as a preprocessing step. GNP represents its individuals using graph structures and evolve them in order to find a solution; this feature contributes to creating quite compact programs and implicitly memorizing past action sequences. In the proposed method using GNP, the significance of the extracted association rule is measured by the use of the chi-squared test and only important association rules are stored in a pool all together through generations. Results of experiments conducted on a real life database suggest that the proposed method provides an effective technique for handling continuous attributes.

本文言語English
ホスト出版物のタイトル2007 IEEE Congress on Evolutionary Computation, CEC 2007
ページ1311-1317
ページ数7
DOI
出版ステータスPublished - 2007 12 1
イベント2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
継続期間: 2007 9 252007 9 28

出版物シリーズ

名前2007 IEEE Congress on Evolutionary Computation, CEC 2007

Conference

Conference2007 IEEE Congress on Evolutionary Computation, CEC 2007
国/地域Singapore
Period07/9/2507/9/28

ASJC Scopus subject areas

  • 人工知能
  • ソフトウェア
  • 理論的コンピュータサイエンス

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