Title :
Evolving Classification Rules by Unconstrained Gene Expression Programming
Author :
Zhang, Jianwei ; Wu, Zhijian ; Guo, Jinglei ; Peng, Min ; Zhang, Yingjiang ; Wang, Chunzhi
Author_Institution :
State Key Lab. of Software Eng., Wuhan Univ., Wuhan
Abstract :
Unconstrained Gene Expression Programming (UGEP), a new unconstrained linear encoded Gene Expression Programming (GEP), is introduced and applied to solve classification problems in this paper. Different from GEP, both amount and length of the genes are dynamically adjusted in the UGEP chromosome during the evolution process. Experiment results indicate that UGEP perform better than GEP in classification problems.
Keywords :
data mining; classification rules; data mining; unconstrained gene expression programming; Biological cells; Classification tree analysis; Data mining; Decision trees; Evolutionary computation; Gene expression; Genetic programming; Laboratories; Linear programming; Testing;
Conference_Titel :
Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3893-8
Electronic_ISBN :
978-1-4244-3894-5
DOI :
10.1109/IWISA.2009.5072858
