Ivan O. Kyrgyzov

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In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particularly adapted to the use of kernel K-means clustering algorithm. Its formulation is based on the definition of MDL derived for Gaussian Mixture Model (GMM). We demonstrate the(More)
Satellite images are numerous and weakly exploited: it is urgent to develop efficient and fast indexing algorithms to facilitate their access. In order to determinate the best features to be extracted, we propose a methodology based on automatic feature selection algorithms, applied unsupervisingly on a strongly redundant features set. In this article we(More)
An algorithm for combining results of different cluster-ings is presented in this paper, the objective of which is to find groups of patterns which are common to all clus-terings. The idea of the proposed combination is to group those samples which are in the same cluster in most cases. We formulate the combination as the resolution of a linear set of(More)
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