148 search results - page 24 / 30 » Discriminative parameter learning for Bayesian networks |
69
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ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
ECML
2006
Springer
15 years 1 months ago
2006
Springer
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
RECOMB
2003
Springer
15 years 10 months ago
2003
Springer
Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which i...
ECSQARU
2001
Springer
15 years 2 months ago
2001
Springer
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
123
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BMCBI
2007
14 years 9 months ago
2007
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...