Rule Induction for Classification Using Multi-objective Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{conf/emo/ReynoldsI06,

• author = "Alan Paul Reynolds and Beatriz {de la Iglesia}",
• title = "Rule Induction for Classification Using Multi-objective Genetic Programming",
• booktitle = "Fourth International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007",
• year = "2007",
• editor = "Shigeru Obayashi and Kalyanmoy Deb and Carlo Poloni and Tomoyuki Hiroyasu and Tadahiko Murata",
• volume = "4403",
• series = "Lecture Notes in Computer Science",
• pages = "516--530",
• address = "Matsushima, Japan",
• month = mar # " 5-8",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "3-540-70927-4",
• DOI = "doi:10.1007/978-3-540-70928-2_40",
• size = "15 pages",
• abstract = "Multi-objective metaheuristics have previously been applied to partial classification, where the objective is to produce simple, easy to understand rules that describe subsets of a class of interest. While this provides a useful aid in descriptive data mining, it is difficult to see how the rules produced can be combined usefully to make a predictive classifier. This paper describes how, by using a more complex representation of the rules, it is possible to produce effective classifiers for two class problems. Furthermore, through the use of multi-objective genetic programming, the user can be provided with a selection of classifiers providing different trade-offs between the misclassification costs and the overall model complexity.",
• notes = "http://www.is.doshisha.ac.jp/emo2007/ old",
• bibdate = "2007-05-21",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/emo/emo2006.html#ReynoldsI06",

}

Genetic Programming entries for Alan Paul Reynolds Beatriz De La Iglesia

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