The threshold EM algorithm for parameter learning in bayesian network with incomplete data
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2011, Vol 2, Issue 7
Abstract
Bayesian networks (BN) are used in a big range of applications but they have one issue concerning parameter learning. In real application, training data are always incomplete or some nodes are hidden. To deal with this problem many learning parameter algorithms are suggested foreground EM, Gibbs sampling and RBE algorithms. In order to limit the search space and escape from local maxima produced by executing EM algorithm, this paper presents a learning parameter algorithm that is a fusion of EM and RBE algorithms. This algorithm incorporates the range of a parameter into the EM algorithm. This range is calculated by the first step of RBE algorithm allowing a regularization of each parameter in bayesian network after the maximization step of the EM algorithm. The threshold EM algorithm is applied in brain tumor diagnosis and show some advantages and disadvantages over the EM algorithm.
Authors and Affiliations
Fradj Ben Lamine , Karim Kalti , Mohamed Ali Mahjoub
Keywords
Related Articles
- EP ID EP150357
- DOI -
- Views 75
- Downloads 0
TokenVote: Secured Electronic Voting System in the Cloud
With the spread of democracy around the world, voting is considered a way to collectively make decisions. Recently, many government offices and private organizations use voting to make decisions when the opinions of mult...
University ERP Preparation Analysis: A PPU Case Study
The Enterprise Resources Planning (ERP) systems are one of the most frequently used systems by business organizations. Recently, the university sectors began using the ERP system in order to increase the quality of their...
School Manager System based on a Personal Information Architecture
The current technological revolution has provided multiple benefits to human activities. For their part, organizations have had the need to make changes to their business requirements, which have led them to migrate to s...
Investigating on Mobile Ad-Hoc Network to Transfer FTP Application
Mobile Ad-hoc Network (MANET) is the collection of mobile nodes without requiring of any infrastructure. Mobile nodes in MANET are operating as a router and MANET network topology can change quickly. Due to nodes in the...
ICT for Education
This paper presents the modeling, design and implementation of a learning platform in Cameroon. This platform contains structured knowledge acquisition modules as well as teaching, learning and assessment modules t...