ADAPTIVE CLUSTERING WITH MISSING VALUES

A. U. Shafronenko, V. V. Volkova, E. V. Bodianskiy

Abstract


In this paper the adaptive neural network system that solves the clustering problem of data with gaps is proposed. This system allows to process the data in the on-line mode with a constant correction of recoverable table’s elements and centers of clusters. A proposed neural system has high speed and simple numerical realization.

Keywords


adaptive neural network system, the restoration of gaps, clustering.

GOST Style Citations






DOI: http://dx.doi.org/10.15588/1607-3274-2011-2-20



Copyright (c) 2014 A. U. Shafronenko, V. V. Volkova, E. V. Bodianskiy

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