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Sondhauss, Ursula
Weihs, Claus
Year of Publication: 
Series/Report no.: 
Technical Report No. 1999,17
We use Dynamic Bayesian networks to classify business cycle phases. We compare classifiers generated by learning the Dynamic Bayesian network structure on different sets of admissible network structures. Included are sets of network structures of the Tree Augmented Naive Bayes (TAN) classifiers of Friedman, Geiger, and Goldszmidt (1997) adapted for dynamic domains. The performance of the developed classifiers on the given data was modest.
Document Type: 
Working Paper

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