A robust deterministic annealing algorithm for data clustering
XL Yang, Q Song, YL Wu - Data & Knowledge Engineering, 2007 - Elsevier
In this paper, a novel robust deterministic annealing (RDA) algorithm is developed for data
clustering. This method takes advantage of conventional noise clustering (NC) and
deterministic annealing (DA) algorithms in terms of the independence of data initialization,
the ability to avoid poor local optima, the better performance for unbalanced data, and the
robustness against noise and outliers. In addition, a cluster validity criterion, ie, Vapnik–
Chervonenkis (VC)-bound induced index, which is estimated based on the structural risk …
clustering. This method takes advantage of conventional noise clustering (NC) and
deterministic annealing (DA) algorithms in terms of the independence of data initialization,
the ability to avoid poor local optima, the better performance for unbalanced data, and the
robustness against noise and outliers. In addition, a cluster validity criterion, ie, Vapnik–
Chervonenkis (VC)-bound induced index, which is estimated based on the structural risk …
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