Pattern Recognition, International Conference on
Download PDF

Abstract

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.
Like what you’re reading?
Already a member?
Get this article FREE with a new membership!

Related Articles