Genetic Programming for Data Classification:
Partitioning the Search Space
J. Eggermont, J. Kok, and W. Kosters. Proceedings of the 2004 Symposium on Applied Computing
(ACM SAC'04), page 1001--1005. Nicosia, Cyprus, (14-17 March 2004)
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.
%0 Conference Paper
%1 EKK04
%A Eggermont, J.
%A Kok, J. N.
%A Kosters, W. A.
%B Proceedings of the 2004 Symposium on Applied Computing
(ACM SAC'04)
%C Nicosia, Cyprus
%D 2004
%K algorithms, classification data genetic programming,
%P 1001--1005
%T Genetic Programming for Data Classification:
Partitioning the Search Space
%U http://www.liacs.nl/~kosters/SAC2003final.pdf
%X 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.
@inproceedings{EKK04,
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.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Nicosia, Cyprus},
author = {Eggermont, J. and Kok, J. N. and Kosters, W. A.},
biburl = {https://www.bibsonomy.org/bibtex/2ce337a9c3c3459c885cd671f698fbea3/brazovayeye},
booktitle = {Proceedings of the 2004 Symposium on Applied Computing
(ACM SAC'04)},
interhash = {4a8ff115fbdea344843f5fbf973ffe8b},
intrahash = {ce337a9c3c3459c885cd671f698fbea3},
keywords = {algorithms, classification data genetic programming,},
month = {14-17 March},
organisation = {ACM},
pages = {1001--1005},
size = {5 pages},
timestamp = {2008-06-19T17:39:08.000+0200},
title = {Genetic Programming for Data Classification:
{P}artitioning the Search Space},
url = {http://www.liacs.nl/~kosters/SAC2003final.pdf},
year = 2004
}