Discovering Comprehensible Classification Rules with a Genetic Algorithm (2000)
| Venue: | In Proc. of the 2000 Congress on Evolutionary Computation |
| Citations: | 25 - 3 self |
BibTeX
@INPROCEEDINGS{Fidelis00discoveringcomprehensible,
author = {M. V. Fidelis and H. S. Lopes and A. A. Freitas and Ponta Grossa},
title = {Discovering Comprehensible Classification Rules with a Genetic Algorithm},
booktitle = {In Proc. of the 2000 Congress on Evolutionary Computation},
year = {2000},
pages = {805--810}
}
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Abstract
This work presents a classification algorithm based on genetic algorithms (GAs) that discovers comprehensible IF-THEN rules, in the spirit of data mining. The proposed GA has a flexible chromosome encoding where each chromosome corresponds to a classification rule. Although the number of genes (genotype) is fixed, the number of rule conditions (phenotype) is variable. The GA also has specific mutation operators for this chromosome encoding. The algorithm was evaluated on two public domain, realworld data sets (on the medical domains of dermatology and breast cancer). 1 Introduction This work presents a system based on genetic algorithms (GAs) to perform the task of classification. The system is evaluated in two medical domains: diagnosis of dermatological diseases and prediction of recurrence of breast cancer. The use of GAs in classification is an attempt to effectively exploit the large search space usually associated with classification tasks. The GA presented here was designed ac...
