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Cluster number selection for a small set of samples using the Bayesian Ying-Yang model

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3 Author(s)
Ping Guo ; Dept. of Comput. Sci., Beijing Normal Univ., China ; Chen, C.L.P. ; Lyu, M.R.

One major problem in cluster analysis is the determination of the number of clusters. In this paper, we describe both theoretical and experimental results in determining the cluster number for a small set of samples using the Bayesian-Kullback Ying-Yang (BYY) model selection criterion. Under the second-order approximation, we derive a new equation for estimating the smoothing parameter in the cost function. Finally, we propose a gradient descent smoothing parameter estimation approach that avoids complicated integration procedure and gives the same optimal result

Published in:

Neural Networks, IEEE Transactions on  (Volume:13 ,  Issue: 3 )

Date of Publication:

May 2002

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