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MICAI
2007
Springer
15 years 5 months ago
Building Fine Bayesian Networks Aided by PSO-Based Feature Selection
A successful interpretation of data goes through discovering crucial relationships between variables. Such a task can be accomplished by a Bayesian network. The dark side is that, ...
María del Carmen Chávez, Gladys Casa...
ICTAI
2005
IEEE
15 years 4 months ago
A Dynamic Bayesian Network for Handling Uncertainty in a Decision Support System Adapted to the Monitoring of Patients Treated b
Telemedicine is a mean of facilitating the distribution of human resources and professional competences. It can speed up diagnosis and therapeutic care delivery and allow peripher...
Cédric Rose, Cherif Smaili, François...
IJCAI
2007
15 years 21 days 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 ...
ML
2008
ACM
222views Machine Learning» more  ML 2008»
14 years 11 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
ML
2006
ACM
142views Machine Learning» more  ML 2006»
14 years 11 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....