253 search results - page 4 / 51 » Learning Bayesian Networks by Evolution for Classifier Combi... |
IFIP12
2008
13 years 8 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...
ICML
2006
IEEE
14 years 7 months ago
2006
IEEE
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
ICML
2004
IEEE
14 years 7 months ago
2004
IEEE
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
ICML
2000
IEEE
14 years 7 months ago
2000
IEEE
Although Bayesian model averaging is theoretically the optimal method for combining learned models, it has seen very little use in machine learning. In this paper we study its app...
ICASSP
2011
IEEE
12 years 10 months ago
2011
IEEE
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...