Hierarchical mixture of discriminative Generalized Dirichlet classifiers

Fuente: arXiv
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Main Authors: Togban, Elvis, Ziou, Djemel
Format: Preprint
Published: 2024
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author Togban, Elvis
Ziou, Djemel
author_facet Togban, Elvis
Ziou, Djemel
contents This paper presents a discriminative classifier for compositional data. This classifier is based on the posterior distribution of the Generalized Dirichlet which is the discriminative counterpart of Generalized Dirichlet mixture model. Moreover, following the mixture of experts paradigm, we proposed a hierarchical mixture of this classifier. In order to learn the models parameters, we use a variational approximation by deriving an upper-bound for the Generalized Dirichlet mixture. To the best of our knownledge, this is the first time this bound is proposed in the literature. Experimental results are presented for spam detection and color space identification.
format Preprint
id arxiv_https___arxiv_org_abs_2405_01778
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hierarchical mixture of discriminative Generalized Dirichlet classifiers
Togban, Elvis
Ziou, Djemel
Machine Learning
This paper presents a discriminative classifier for compositional data. This classifier is based on the posterior distribution of the Generalized Dirichlet which is the discriminative counterpart of Generalized Dirichlet mixture model. Moreover, following the mixture of experts paradigm, we proposed a hierarchical mixture of this classifier. In order to learn the models parameters, we use a variational approximation by deriving an upper-bound for the Generalized Dirichlet mixture. To the best of our knownledge, this is the first time this bound is proposed in the literature. Experimental results are presented for spam detection and color space identification.
title Hierarchical mixture of discriminative Generalized Dirichlet classifiers
topic Machine Learning
url https://arxiv.org/abs/2405.01778