Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CCBD.2014.21 | CCBD |
Keywords | Field | DocType |
pattern clustering,clustering algorithm,multi-objective,multiobjective clustering algorithm,clustering algorithm, gene expression programming, multi-objective,clustering number,mogep-cluster algorithm,multiobjective cluster algorithm,genetic algorithms,single-objective clustering algorithm,data mining,gep-cluster algorithm,gene expression programming,statistics,encoding,gene expression,sociology,algorithm design and analysis,clustering algorithms | Canopy clustering algorithm,Data mining,Fuzzy clustering,Clustering high-dimensional data,CURE data clustering algorithm,Data stream clustering,Correlation clustering,Computer science,Determining the number of clusters in a data set,Artificial intelligence,Cluster analysis,Machine learning | Conference |
ISSN | Citations | PageRank |
2378-3680 | 0 | 0.34 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Youcong Ni | 1 | 18 | 8.10 |
| Xin Du | 2 | 127 | 26.78 |
| Datong Xie | 3 | 20 | 3.12 |
| Peng Ye | 4 | 8 | 2.59 |
| Kaihuo Zhang | 5 | 0 | 0.34 |