A New Hierarchical Clustering Method using Topological Map
Méziane Yacoub, Ndeye Niang Keita, Fouad Badran, Sylvie Thiria · HAL (Le Centre pour la Communication Scientifique Directe) · 2001
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 different 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 effect of this criteria for different values of T.