Title :
A Preliminary Study on Constructing Decision Tree with Gene Expression Programming
Author :
Wang, Weihong ; Li, Qu ; Han, Shanshan ; Lin, Hai
Author_Institution :
Coll. of Software Eng., Zhejiang Univ. of Technol., Hangzhou
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
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 IDS
Keywords :
decision trees; genetic algorithms; pattern classification; data mining; decision tree; evolutionary computation; gene expression programming; genetic algorithm; pattern classification; Classification tree analysis; Computer science; Decision trees; Distributed computing; Educational institutions; Gene expression; Genetic algorithms; Geology; Software engineering; Testing;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.22