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» Learning Bayesian Networks with qualitative constraints
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ICPR
2008
IEEE
15 years 11 months ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao
EKAW
2004
Springer
15 years 3 months ago
Designing a Procedure for the Acquisition of Probability Constraints for Bayesian Networks
Among the various tasks involved in building a Bayesian network for a real-life application, the task of eliciting all probabilities required is generally considered the most daunt...
Eveline M. Helsper, Linda C. van der Gaag, Floris ...
ITRE
2005
IEEE
15 years 3 months ago
Structure learning of Bayesian networks using a semantic genetic algorithm-based approach
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
Sachin Shetty, Min Song
IJCAI
2007
14 years 11 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...