A Fully Bayesian Inference with Gibbs Sampling for Finite and Infinite Discrete Exponential Mixture Models

In this paper, we propose clustering algorithms based on finite mixture and infinite mixture models of exponential approximation to the Multinomial Generalized Dirichlet (EMGD), Multinomial Beta-Liouville (EMBL) and Multinomial Shifted-Scaled Dirichlet (EMSSD) with Bayesian inference. The finite mix...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Applied artificial intelligence 2022-12, Vol.36 (1)
Hauptverfasser:	Su, Xuanbo, Zamzami, Nuha, Bouguila, Nizar
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian analysis Clustering Data mining Dirichlet problem Mixtures Monte Carlo simulation Sampling Statistical inference
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!