Chrisman, L., A roadmap to Research on Bayesian networks and other decomposable probabilistic models, technical report, School of Computer Science, CMU, 1996. Home/Search Document Details and Download
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Learning Bayesian Networks from Data: An Efficient Approach.. - Cheng, Bell, Liu (1997) (4 citations) (Correct)
....models include Bayesian networks and Markov networks. In recent years, graphical model learning has become a very active research topic and many algorithms have been developed for it. For survey papers and introductory papers on probabilistic network learning, please refer to [Buntine, 1996; Chrisman, 1996; Heckerman, 1995; Krause, 1996] There are two general approaches to graphical probabilistic model learning from data, the search scoring methods and the dependency analysis methods. In the first approach, the algorithms view the learning problem as to search for a structure that can fit the ....
Chrisman, L., A roadmap to Research on Bayesian networks and other decomposable probabilistic models, technical report, School of Computer Science, CMU, 1996.
Learning Bayesian Networks from Data: - An Information-Theory Based (Correct)
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Chrisman, L., A roadmap to Research on Bayesian networks and other decomposable probabilistic models, technical report, School of Computer Science, CMU, 1996.
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