International Journal of Computational Intelligence Systems

Volume 7, Issue Supplement 1, January 2014, Pages 6 - 17

Implicit parameter estimation for conditional Gaussian Bayesian networks

Authors
Aida Jarraya, Philippe Leray, Afif Masmoudi
Corresponding Author
Aida Jarraya
Received 12 June 2012, Accepted 7 August 2013, Available Online 1 January 2014.
DOI
https://doi.org/10.1080/18756891.2014.853926How to use a DOI?
Keywords
Conditional Gaussian Bayesian networks, Bayesian estimation, Implicit estimation, Parameter learning
Abstract
The Bayesian estimation of the conditional Gaussian parameter needs to define several a priori parameters. The proposed approach is free from this definition of priors. We use the Implicit estimation method for learning from observations without a prior knowledge. We illustrate the interest of such an estimation method by giving first the Bayesian Expectation A Posteriori estimator for conditional Gaussian parameters. Then, we describe the Implicit estimators for the same parameters. Moreover, an experimental study is proposed in order to compare both approaches.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Journal
International Journal of Computational Intelligence Systems
Volume-Issue
7 - 100
Pages
6 - 17
Publication Date
2014/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.1080/18756891.2014.853926How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Aida Jarraya
AU  - Philippe Leray
AU  - Afif Masmoudi
PY  - 2014
DA  - 2014/01
TI  - Implicit parameter estimation for conditional Gaussian Bayesian networks
JO  - International Journal of Computational Intelligence Systems
SP  - 6
EP  - 17
VL  - 7
IS  - Supplement 1
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2014.853926
DO  - https://doi.org/10.1080/18756891.2014.853926
ID  - Jarraya2014
ER  -