Extended Genetic Programming Using Apriori Algorithm for Rule Discovery

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{Niimi:2001:EGP,

• author = "Ayahiko Niimi and Eiichiro Tazaki",
• title = "Extended Genetic Programming Using Apriori Algorithm for Rule Discovery",
• booktitle = "New Frontiers in Artificial Intelligence : Joint JSAI 2001 Workshop Post-Proceedings",
• year = "2001",
• editor = "T. Terano and T. Nishida and A. Namatame and S. Tsumoto and Y. Ohsawa and T. Washio",
• volume = "2253",
• series = "Lecture Notes in Computer Science",
• pages = "525--532",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-43070-4",
• CODEN = "LNCSD9",
• ISSN = "0302-9743",
• bibdate = "Sat Feb 2 13:07:38 MST 2002",
• DOI = "doi:10.1007/3-540-45548-5_73",
• acknowledgement = ack-nhfb,
• abstract = "Genetic programming (GP) usually has a wide search space and can use tree structure as its chromosome expression. So, GP may search for global optimum solution. But, in general, GP's learning speed is not so fast. Apriori algorithm is one of algorithms for generation of association rules. It can be applied to large database. But, It is difficult to define its parameters without experience. We propose a rule discovery technique from a database using GP combined with association rule algorithm. It takes rules generated by the association rule algorithm as initial individual of GP. The learning speed of GP is improved by the combined algorithm. To verify the effectiveness of the proposed method, we apply it to the meningoencephalitis diagnosis activity data in a hospital. We got domain expert's comments on our results. We discuss the result of proposed method with prior ones.",

}

Genetic Programming entries for Ayahiko Niimi Eiichiro Tazaki

Citations