A Tutorial on Learning With Bayesian Networks

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A Tutorial on Learning With Bayesian Networks (1996) (Make Corrections) (219 citations)
David Heckerman

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Abstract: A Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest. When used in conjunction with statistical techniques, the graph- ical model has several advantages for data analysis. One, because the model encodes dependencies among all variables, it readily handles situations where some data entries are missing. Two, a Bayesian network can be used to learn causal relationships, and hence can be used to gain understanding about a problem domain and... (Update)

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BibTeX entry: (Update)

David Heckerman. A tutorial on learning with bayesian networks. Technical Report MSR-TR-95-06, Microsoft Research, Redmond, Washington, 1995. Revised June 96. http://citeseer.ist.psu.edu/article/heckerman96tutorial.html More

@misc{ heckerman95tutorial,
  author = "D. Heckerman",
  title = "A tutorial on learning with bayesian networks",
  text = "David Heckerman. A tutorial on learning with bayesian networks. Technical
    Report MSR-TR-95-06, Microsoft Research, Redmond, Washington, 1995. Revised
    June 96.",
  year = "1995",
  url = "citeseer.ist.psu.edu/article/heckerman96tutorial.html" }

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