Self-adaptive mechanism in genetic network programming for mining association rules

Karla Taboada, Kaoru Shimada, Shingo Mabu, Kotaro Hirasawa, Takayuki Furuzuki

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

1 Citation (Scopus)

Abstract

In this paper we propose a method of association rule mining using Genetic Network Programming (GNP) with a self-adaptation mechanism in order to improve the performance of association rule extraction systems. GNP is a kind of evolutionary methods, whose directed graphs are evolved to find a solution as individuals. Self-adaptation behavior in GNP is related to adjust the setting of control parameters such as crossover and mutation rates. It is called self-adaptive because the algorithm controls the setting of these parameters itself - embedding them into an individual's genome and evolving them. The aim is not only to find suitable adjustments but to do this efficiently. Our method can measure the significance of the association via the chi-squared test and obtain a sufficient number of important association rules. Extracted association rules are stored in a pool all together through generations and reflected in three genetic operators as acquired information. Further, our method can contain negation of attributes in association rules and suit association rule mining from dense databases.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages6007-6012
Number of pages6
DOIs
Publication statusPublished - 2006
Event2006 SICE-ICASE International Joint Conference - Busan
Duration: 2006 Oct 182006 Oct 21

Other

Other2006 SICE-ICASE International Joint Conference
CityBusan
Period06/10/1806/10/21

Fingerprint

Association rules
Directed graphs
Genes

Keywords

  • Association rules
  • Data mining
  • Evolutionary computation
  • Genetic network programming
  • Self-adaptation

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Taboada, K., Shimada, K., Mabu, S., Hirasawa, K., & Furuzuki, T. (2006). Self-adaptive mechanism in genetic network programming for mining association rules. In 2006 SICE-ICASE International Joint Conference (pp. 6007-6012). [4108654] https://doi.org/10.1109/SICE.2006.315846

Self-adaptive mechanism in genetic network programming for mining association rules. / Taboada, Karla; Shimada, Kaoru; Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki.

2006 SICE-ICASE International Joint Conference. 2006. p. 6007-6012 4108654.

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

Taboada, K, Shimada, K, Mabu, S, Hirasawa, K & Furuzuki, T 2006, Self-adaptive mechanism in genetic network programming for mining association rules. in 2006 SICE-ICASE International Joint Conference., 4108654, pp. 6007-6012, 2006 SICE-ICASE International Joint Conference, Busan, 06/10/18. https://doi.org/10.1109/SICE.2006.315846
Taboada K, Shimada K, Mabu S, Hirasawa K, Furuzuki T. Self-adaptive mechanism in genetic network programming for mining association rules. In 2006 SICE-ICASE International Joint Conference. 2006. p. 6007-6012. 4108654 https://doi.org/10.1109/SICE.2006.315846
Taboada, Karla ; Shimada, Kaoru ; Mabu, Shingo ; Hirasawa, Kotaro ; Furuzuki, Takayuki. / Self-adaptive mechanism in genetic network programming for mining association rules. 2006 SICE-ICASE International Joint Conference. 2006. pp. 6007-6012
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