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
fDate :
31 July-4 Aug. 2005
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;
Conference_Titel :
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN :
0-7803-9048-2
DOI :
10.1109/IJCNN.2005.1556166
