DocumentCode
446028
Title
A robust deterministic annealing algorithm for data clustering
Author
Yang, Xulei ; Song, Qing ; Liu, Sheng
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume
3
fYear
2005
fDate
31 July-4 Aug. 2005
Firstpage
1878
Abstract
In this paper, a new robust deterministic annealing (RDA) clustering algorithm is proposed. This method takes advantages of conventional noise clustering (NC) and deterministic annealing (DA) algorithms in terms of independence of data initialization, ability to avoid poor local optima, better performance for unbalanced data, and robustness against noise. The superiority of the proposed RDA clustering algorithm is supported by simulation results.
Keywords
data analysis; deterministic algorithms; pattern clustering; simulated annealing; RDA clustering algorithm; data clustering; data initialization; noise clustering; robust deterministic annealing algorithm; Annealing; Clustering algorithms; Data analysis; Data engineering; Noise robustness; Partitioning algorithms; Pattern recognition; Phase change materials; Probability distribution; Prototypes;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN
0-7803-9048-2
Type
conf
DOI
10.1109/IJCNN.2005.1556166
Filename
1556166
Link To Document