Genetic Programming for Data Classification: Partitioning the Search Space

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{eggermont:2004:sac,

• author = "Jeroen Eggermont and Joost N. Kok and Walter A. Kosters",
• title = "Genetic Programming for Data Classification: Partitioning the Search Space",
• booktitle = "Proceedings of the 2004 Symposium on applied computing (ACM SAC'04)",
• year = "2004",
• pages = "1001--1005",
• address = "Nicosia, Cyprus",
• month = "14-17 " # mar,
• keywords = "genetic algorithms, genetic programming, data classification",
• URL = "http://www.liacs.nl/~kosters/SAC2003final.pdf",
• DOI = "doi:10.1145/967900.968104",
• size = "5 pages",
• abstract = "When Genetic Programming is used to evolve decision trees for data classification, search spaces tend to become extremely large. We present several methods using techniques from the field of machine learning to refine and thereby reduce the search space sizes for decision tree evolvers. We will show that these refinement methods improve the classification performance of our algorithms.",

}

Genetic Programming entries for Jeroen Eggermont Joost Kok Walter A Kosters

Citations