Innovative Computing ,Information and Control, International Conference on (2006)
Aug. 30, 2006 to Sept. 1, 2006
Weihong Wang , Zhejiang University of Technology, China
Qu Li , Zhejiang University of Technology, China
Shanshan Han , Zhejiang University of Technology, China
Hai Lin , China University of Geosciences, China
Gene expression programming (GEP) is a kind of genotype/phenotype based genetic algorithm. Its successful application in classification rules mining has gained wide interest in data mining and evolutionary computation fields. However, current GEP based classifiers represent classification rules in the form of expression tree, which is less meaningful and expressive than decision tree. What?s more, these systems adopt one-against-all learning strategy, i.e. to solve a n-class with n runs, each run solving a binary classification task. In this paper, a GEP decision tree(GEPDT) system is presented, the system can construct a decision tree for classification without priori knowledge about the distribution of data, at the same time, GEPDT can solve a n-class problem in a single run, preliminary results show that the performance of GEP based decision tree is comparable to ID3.
Q. Li, W. Wang, H. Lin and S. Han, "A Preliminary Study on Constructing Decision Tree with Gene Expression Programming," First International Conference on Innovative Computing, Information and Control(ICICIC), Beijing, 2006, pp. 222-225.