Title :
Supervised classification using MCMC methods
Author :
Davy, Manuel ; Doncarli, Christian ; Tourneret, Jean-Yves
Author_Institution :
IRCyN, Nantes, France
Abstract :
This paper addresses the problem of supervised classification using general Bayesian learning. General Bayesian learning consists of estimating the unknown class-conditional densities from a set of labelled samples. However, the estimation requires to evaluate intractable multidimensional integrals. This paper studies an implementation of general Bayesian learning based on Markov chain Monte Carlo (MCMC) methods
Keywords :
Bayes methods; Markov processes; Monte Carlo methods; learning (artificial intelligence); learning systems; parameter estimation; signal classification; Bayesian learning; MCMC methods; Markov chain Monte Carlo methods; intractable multidimensional integrals; labelled samples; supervised classification; unknown class-conditional densities; Bayesian methods; Bismuth; Chirp; Closed-form solution; Decision theory; Monte Carlo methods; Multidimensional signal processing; Multidimensional systems; Probability density function; Supervised learning;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
0-7803-6293-4
DOI :
10.1109/ICASSP.2000.861854
