Class association rule mining with chi-squared test using Genetic Network Programming

Kaoru Shimada, Kotaro Hirasawa, Takayuki Furuzuki

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

55 Citations (Scopus)

Abstract

An efficient algorithm for important class association rule mining using Genetic Network Programming (GNP) is proposed. GNP is one of the evolutionary optimization techniques, which uses directed graph structures as genes. Instead of generating a large number of candidate rules, the method can obtain a sufficient number of important association rules for classification. The proposed method measures the significance of the association via the chi-squared test. Therefore, all the extracted important rules can be used for classification directly. In addition, the method suits class association rule mining from dense databases, where many frequently occurring items are found in each tuple. Users can define conditions of extracting important class association rules. In this paper, we describe an algorithm for class association rule mining with chi-squared test using GNP and present a classifier using these extracted rules.

Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages5338-5344
Number of pages7
Volume6
DOIs
Publication statusPublished - 2007
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei
Duration: 2006 Oct 82006 Oct 11

Other

Other2006 IEEE International Conference on Systems, Man and Cybernetics
CityTaipei
Period06/10/806/10/11

Fingerprint

Association rules
Directed graphs
Classifiers
Genes

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Shimada, K., Hirasawa, K., & Furuzuki, T. (2007). Class association rule mining with chi-squared test using Genetic Network Programming. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (Vol. 6, pp. 5338-5344). [4274766] https://doi.org/10.1109/ICSMC.2006.385157

Class association rule mining with chi-squared test using Genetic Network Programming. / Shimada, Kaoru; Hirasawa, Kotaro; Furuzuki, Takayuki.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 6 2007. p. 5338-5344 4274766.

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

Shimada, K, Hirasawa, K & Furuzuki, T 2007, Class association rule mining with chi-squared test using Genetic Network Programming. in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. vol. 6, 4274766, pp. 5338-5344, 2006 IEEE International Conference on Systems, Man and Cybernetics, Taipei, 06/10/8. https://doi.org/10.1109/ICSMC.2006.385157
Shimada K, Hirasawa K, Furuzuki T. Class association rule mining with chi-squared test using Genetic Network Programming. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 6. 2007. p. 5338-5344. 4274766 https://doi.org/10.1109/ICSMC.2006.385157
Shimada, Kaoru ; Hirasawa, Kotaro ; Furuzuki, Takayuki. / Class association rule mining with chi-squared test using Genetic Network Programming. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 6 2007. pp. 5338-5344
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