Evolutionary operation setting for outcome accumulation type evolutionary rule discovery method

Author:

Matsuno Shogo1,Shimada Kaoru1

Affiliation:

1. Gunma University, Maebashi, Gunma, JAPAN

Funder

Japan Society for the Promotion of Science

Publisher

ACM

Reference10 articles.

1. Rakesh Agrawal , Ramakrishnan Srikant , 1994 . Fast algorithms for mining association rules . In Proc. 20th int. conf. very large data bases, VLDB , Vol. 1215 . Citeseer, 487--499. Rakesh Agrawal, Ramakrishnan Srikant, et al. 1994. Fast algorithms for mining association rules. In Proc. 20th int. conf. very large data bases, VLDB, Vol. 1215. Citeseer, 487--499.

2. Lakhmi. C. Jain Ashish. Ghosh. 2005. Springer Berlin Heidelberg. Lakhmi. C. Jain Ashish. Ghosh. 2005. Springer Berlin Heidelberg.

3. C. Blake and C. Merz. 1998. UCI Repository of Machine Learning Databases. Retrieved February 3 2022 from http://www.ics.uci.edu/~mlearn/MLRepository.html C. Blake and C. Merz. 1998. UCI Repository of Machine Learning Databases. Retrieved February 3 2022 from http://www.ics.uci.edu/~mlearn/MLRepository.html

4. Network Structure Oriented Evolutionary Model: Genetic Network Programming

5. Shingo Mabu , Ci Chen , Nannan Lu , Kaoru Shimada , and Kotaro Hirasawa . 2010. An intrusion-detection model based on fuzzy class-association-rule mining using genetic network programming . IEEE transactions on systems, man, and cybernetics, part C (Applications and Reviews) 41, 1 ( 2010 ), 130--139. Shingo Mabu, Ci Chen, Nannan Lu, Kaoru Shimada, and Kotaro Hirasawa. 2010. An intrusion-detection model based on fuzzy class-association-rule mining using genetic network programming. IEEE transactions on systems, man, and cybernetics, part C (Applications and Reviews) 41, 1 (2010), 130--139.

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