Multi-objective Techniques in Genetic Programming for Evolving Classifiers

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

@InProceedings{parrott:2005:CEC,

• author = "Daniel Parrott and Xiaodong Li and Vic Ciesielski",
• title = "Multi-objective Techniques in Genetic Programming for Evolving Classifiers",
• booktitle = "Proceedings of the 2005 IEEE Congress on Evolutionary Computation",
• year = "2005",
• editor = "David Corne and Zbigniew Michalewicz and Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and Garrison Greenwood and Tan Kay Chen and Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and Jennifier Willies and Juan J. Merelo Guervos and Eugene Eberbach and Bob McKay and Alastair Channon and Ashutosh Tiwari and L. Gwenn Volkert and Dan Ashlock and Marc Schoenauer",
• volume = "2",
• pages = "1141--1148",
• address = "Edinburgh, UK",
• publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
• month = "2-5 " # sep,
• organisation = "IEEE Computational Intelligence Society, Institution of Electrical Engineers (IEE), Evolutionary Programming Society (EPS)",
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "0-7803-9363-5",
• URL = "http://goanna.cs.rmit.edu.au/~xiaodong/publications/183.pdf",
• DOI = "doi:10.1109/CEC.2005.1554819",
• abstract = "The application of multi-objective evolutionary computation techniques to the genetic programming of classifiers has the potential to both improve the accuracy and decrease the training time of the classifiers. The performance of two such algorithms are investigated on the even 6-parity problem and the Wisconsin Breast Cancer, Iris and Wine data sets from the UCI repository. The first method explores the addition of an explicit size objective as a parsimony enforcement technique. The second represents a program's classification accuracy on each class as a separate objective. Both techniques give a lower error rate with less computational cost than was achieved using a standard GP with the same parameters.",
• notes = "CEC2005 - A joint meeting of the IEEE, the IEE, and the EPS.",

}

Genetic Programming entries for Daniel Parrott Xiaodong Li Victor Ciesielski

Citations