SOFT CLUSTERING ALGORITHM BASED ON SEPARATING HYPERSURFACES

О. І. Chumachenko, V. S. Gorbatiuk

Abstract


A new “soft” clustering algorithm is proposed based on the use of artificial neural networks as  models of hypersurfaces that separate clusters. The algorithm allows to solve the problem of soft clusterization as a problem of smooth nonlinear function optimization and, therefore, to apply the entire mathematical apparatus of nonlinear optimization, which has evolved significantly in recent years. 

Keywords


Clustering; artificial neural networks; soft clustering; nonlinear optimization.

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