Theory of a Probabilistic-Dependence Measure of Dissimilarity Among Multiple Clusters

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Conference object , Article 01 Jan 2006Publisher:Springer Berlin Heidelberg

Authors: Kazunori Iwata 0001; Akira Hayashi;

doi: 10.1007/11840930_32

Theory of a Probabilistic-Dependence Measure of Dissimilarity Among Multiple Clusters

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Abstract

We introduce novel dissimilarity to properly measure dissimilarity among multiple clusters when each cluster is characterized by a probability distribution. This measure of dissimilarity is called redundancy-based dissimilarity among probability distributions. From aspects of source coding, a statistical hypothesis test and a connection with Ward's method, we shed light on the theoretical reasons that the redundancy-based dissimilarity among probability distributions is a reasonable measure of dissimilarity among clusters.

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Hiroshima City University
Japan

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