377 search results - page 1 / 76 » Learning Bayesian networks from data: An information-theory ... |
CIKM
1997
Springer
13 years 9 months ago
1997
Springer
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
AI
2002
Springer
13 years 4 months ago
2002
Springer
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
AIIA
2003
Springer
13 years 10 months ago
2003
Springer
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
CORR
2004
Springer
13 years 4 months ago
2004
Springer
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...
IFIP12
2008
13 years 6 months ago
2008
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...