clustering, cluster stability, randomized algorithms, stochastic approximation, simultaneous perturbation, on-line algorithms. " />

RANDOMIZED METHOD OF FINDING THE NUMBER OF CLUSTERS IN A DATA SET

D. . Shalymov


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Abstract

 

New non-parametric method of choosing the number of groups in a data set is proposed. It is based on
randomized stochastic approximation algorithm with input artificial perturbation. Main features to keep
convergence under almost arbitrary noise are described. Proposed method could be used for on-line clustering of
dynamically changed data sets. The effectiveness is demonstrated on a wide range of simulated and real nature
data sets.

Keywords:   clustering, cluster stability, randomized algorithms, stochastic approximation, simultaneous perturbation, on-line algorithms.
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