DocumentCode :
3579175
Title :
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
Link To Document :
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