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Fuzzy Topographic Kernel Clustering
Citation key Graepel1998a
Author Graepel, T. and Obermayer, K.
Title of Book Proceedings of the 5th GI Workshop Fuzzy Neuro Systems
Pages 90 – 97
Year 1998
Editor W. Brauer
Abstract A new topographic clustering algorithm is proposed, which – by the use of integral operator kernel functions – efficiently estimates the centers of clusters in a high-dimensional feature space, which is related to data space by some non linear map. Like in the Self-Organizing Map topography is imposed by assuming finite transition probabilities between cluster indices. The optimization of the associated cost function is achieved by estimating the parameters via an EM-scheme and determini stic annealing. The effect of different radial basis function kernels on topographic maps of handwritten digit data is examined in computer simulations.
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