An Evolutionary Method for Associative Contrast Rule Mining from Incomplete Database
Kaoru Shimada and Takashi Hanioka
Fukuoka Dental College
2-15-1 Tamura, Sawara-ku, Fukuoka 814-0193, Japan
-  R. Agrawal and R. Srikant, “Fast Algorithms for Mining Association Rules,” Proc. of the 20th VLDB Conf., pp. 487-499, 1994.
-  J. Han, J. Pei, Y. Yin and R. Mao, “Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach,” Data Mining and Knowledge Discovery, Vol.8, pp. 53-87, 2004.
-  X. Wu, C. Zhang and S. Zhang, “Efficient Mining of Both Positive and Negative Association Rules,” ACM Trans. on Information Systems, Vol.22, No.3, pp. 381-405, 2004.
-  A. K. H. Tung, H. Lu, J. Han and L. Feng, “Efficient Mining of Intertransaction Association Rules,” IEEE Trans. on Knowledge and Data Engineering Vol.15, No.1, pp. 43-56, 2003.
-  K. Shimada and K. Hirasawa, “Exceptional Association Rule Mining Using Genetic Network Programming,” Proc. of the 4th Int. Conf. on Data Mining (DMIN), pp. 277-283, 2008.
-  K. Shimada and T. Hanioka, “An Evolutionary Associative Contrast Rule Mining Method for Incomplete Database,” Proc. of the Int. Conf. on Data Mining (DMIN), pp. 160-166, 2013.
-  J. W. Grzymala-Busse and W. J. Grzymala-Busse, “Handling Missing Attribute Values,” Data Mining and Knowledge Discovery Handbook (2nd ed.), O. Maimon, L. Rockach (eds.), Springer, pp. 33-51, 2010.
-  M. Saar-Tsechansky and F. Provost, “Handling Missing Values when Applying Classification Models,” J. of Machine Learning Research, Vol.8, pp. 1625-1657, 2007.
-  K. Shimada and K. Hirasawa, “A Method of Association Rule Analysis for Incomplete Database Using Genetic Network Programming,” Proc. of the Genetic and Evolutionary Computation Conf. (GECCO 2010), pp. 1115-1122, 2010.
-  K. Shimada, “An Evolving Associative Classifier for Incomplete Database,” Lecture Notes in Artificial Intelligence, Vol.7377: Advances in Data Mining, Perner P.(Ed.), Springer, pp. 136-150, 2012.
-  K. Shimada and T. Hanioka, “An Evolutionary Method for Exceptional Association Rule Set Discovery from Incomplete Database,” Proc. of Int. Conf. on Information Technology in Bio- and Medical Informatics (ITBAM), Lecture Notes in Computer Science, Vol.8649, M. Bursa et al. (Eds.), Springer, pp. 133-147, 2014.
-  S. Mabu, C. Chen, N. Lu, K. Shimada, and K. Hirasawa, “An Intrusion-Detection Model Based on Fuzzy Class-Association-Rule Mining Using Genetic Network Programming,” IEEE Trans. on Systems, Man, and Cybernetics – Part C –, Vol.41, pp. 130-139, 2011.
-  S. Mabu, K. Hirasawa, and J. Hu, “A Graph-Based Evolutionary Algorithm: Genetic Network Programming (GNP) and Its Extension Using Reinforcement Learning,” Evolutionary Computation, Vol.15, No.3, pp. 369-398, 2007.
-  A. A. Freitas, “Data Mining and knowledge Discovery with Evolutionary Algorithms,” Springer, New York, 2002.
-  A. Ghosh and L. C. Jain, “Evolutionary Computing in Data Mining,” Springer, Heidelberg, 2005.
-  K. Shimada, K. Hirasawa and J. Hu, “Genetic Network Programming with Acquisition Mechanisms of Association Rules,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.10, No.1, pp. 102-111, 2006.
-  S. Brin, R. Motwani, and C. Silverstein, “Beyond market baskets: generalizing association rules to correlations,” Proc. of ACM SIGMOD, pp. 265-276, 1997.
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