DocumentCode :
3472909
Title :
A Hybrid Clustering Algorithm Based on Dimensional Reduction and K-Harmonic Means
Author :
Guo, Chonghui ; Peng, Li
Author_Institution :
Inst. of Syst. Eng., Dalian Univ. of Technol., Dalian
fYear :
2008
fDate :
12-14 Oct. 2008
Firstpage :
1
Lastpage :
4
Abstract :
Clustering analysis is an active and challenge research direction in the field of data mining. In this paper we propose a new clustering algorithm based on dimensional reduction approach and K-harmonic means algorithm. Numerical results illustrate that the new hybrid clustering algorithm has advantages in the computation time, iteration numbers and clustering results in most cases, and it is also an algorithm which is suitable for large scale data sets.
Keywords :
data mining; pattern clustering; K-harmonic means; data mining; dimensional reduction; hybrid clustering algorithm; iteration numbers; Clustering algorithms; Clustering methods; Data mining; Large-scale systems; Mathematics; Measurement standards; Partitioning algorithms; Principal component analysis; Space technology; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
Type :
conf
DOI :
10.1109/WiCom.2008.2644
Filename :
4680833
Link To Document :
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