Difference between revisions of "Heckerman, JMLR 2000"
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== Summary == | == Summary == | ||
| − | + | In this [[Category::paper]], author describe a graphical model for probabilistic relationship, an alternative to the bayesian network, called dependency network. The dependency network, unlike bayesian network is potentially cyclic. The dependency network are well suited to task of predicting preferences like in collaborative filtering. The dependency network is not good for encoding causal relationship. | |
== Brief description of the method == | == Brief description of the method == | ||
Revision as of 17:56, 25 September 2011
Contents
Citation
Dependency Networks for Inference, Collaborative Filtering, and Data Visualization. David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Kadie; in JMLR, 1(Oct):49-75, 2000
Online version
Summary
In this paper, author describe a graphical model for probabilistic relationship, an alternative to the bayesian network, called dependency network. The dependency network, unlike bayesian network is potentially cyclic. The dependency network are well suited to task of predicting preferences like in collaborative filtering. The dependency network is not good for encoding causal relationship.
