论文信息 - A powerful finite mixture model based on the generalized Dirichlet distribution: unsupervised learning and applications

A powerful finite mixture model based on the generalized Dirichlet distribution: unsupervised learning and applications

This paper presents a new finite mixture model based on a generalization of the Dirichlet distribution. For the estimation of the parameters of this mixture we use a GEM (generalized expectation maximization) algorithm based on a Newton-Raphson step. The experimental results involve the comparison of the performance of Gaussian and generalized Dirichlet mixtures in the classification of several pattern-recognition data sets.

Nizar Bouguila | Djemel Ziou | D. Ziou | N. Bouguila

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