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A New Hierarchical Clustering Method using Topological Map

Abstract : We present a new hierarchical clustering criteria which can be applied to data set. This is done after generating an initial partition byusing a Topological Self Organizing Map. This criteria contains two terms which take into account two di erent errors simultaneously: the square error of the entire clustering (as the Ward criteria) and the topological structure given by the Self Organizing Map. A parameter T allows to control the corresponding in uence of these two terms. Results on simulated data are presented which show the e ect of this criteria for different values of T.
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Submitted on : Friday, March 6, 2015 - 10:41:56 AM
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  • HAL Id : hal-01124631, version 1



Meziane Yacoub, Ndeye Niang Keita, Fouad Badran, Sylvie Thiria. A New Hierarchical Clustering Method using Topological Map. 10th Int. Symp. on Applied Stochastique Models and Data Analysis (AMSDA2001),, Jan 2001, X, France. ⟨hal-01124631⟩



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