We propose a measure for assessing the degree of influ- ence of a set of edges of a Bayesian network on the overall fitness of the network, starting with probability distributions extracted from a data set. Standard fitness measures such as the Cooper-Herskowitz score or the score based on the minimum description length are computationally expensive and do not focus on local modifications of networks. Our approach can be used for simplifying the Bayesian network structures without significant loss of fitness. Experimental work confirms the validity of our approach.
|Cite as: Baraty, S. and Simovici, D. A. (2009). Edge Evaluation in Bayesian Network Structures. In Proc. Eighth Australasian Data Mining Conference (AusDM`09) Melbourne, Australia. CRPIT, 101. Kennedy P. J., Ong K. and Christen P. Eds., ACS. 193-200 |
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