34 search results - page 2 / 7 » Learning Bayesian Networks with qualitative constraints |
125
Voted
ICPR
2008
IEEE
16 years 5 months ago
2008
IEEE
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...
91
Voted
IDA
2007
Springer
15 years 10 months ago
2007
Springer
111
Voted
EKAW
2004
Springer
15 years 9 months ago
2004
Springer
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...
157
Voted
ITRE
2005
IEEE
15 years 9 months ago
2005
IEEE
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...
154
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IJCAI
2007
15 years 5 months ago
2007
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...