A Multi-objective Cluster Algorithm Based on GEP

Author

Youcong Ni ; Xin Du ; Datong Xie ; Peng Ye ; Kaihuo Zhang

Author_Institution

State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China

fYear

2014

Firstpage

33

Lastpage

38

Abstract

Clustering is one of the main methods in data mining. Many clustering algorithms have been proposed so far. Among them, GEP-Cluster, a single-objective clustering algorithm, can automatically cluster with unknown clustering number. However, it is difficult for GEP-Cluster to find the high-quality solution in the limited search space. Aiming at the problems, a multi-objective clustering algorithm based on gene expression programming, MOGEP-Cluster, is proposed in this paper. To validate the effectiveness of MOGEP-Cluster, a set of experiments are performed on 5 benchmark datasets. The experimental results show that MOGEP-Cluster can find better solutions than GEP-Cluster.

Keywords

data mining; genetic algorithms; pattern clustering; GEP-Cluster algorithm; MOGEP-Cluster algorithm; clustering number; data mining; gene expression programming; multiobjective cluster algorithm; multiobjective clustering algorithm; single-objective clustering algorithm; Algorithm design and analysis; Clustering algorithms; Encoding; Gene expression; Sociology; Software algorithms; Statistics; Clustering algorithm; Gene expression programming; multi-objective;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Big Data (CCBD), 2014 International Conference on

Type

conf

DOI

10.1109/CCBD.2014.21

Filename

7062869