Abstract
A large part of recent research on probabilistic and possibilistic inference networks has been devoted to learning them from data. In this paper we discuss two search methods and several evaluation measures usable for this task. We consider a scheme for evaluating induced networks and present experimental results obtained from an application of INES (Induction of NEtwork Structures), a prototype implementation of the described methods and measures.
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Borgelt, C., Kruse, R. (1997). Some experimental results on learning probabilistic and possibilistic networks with different evaluation measures. In: Gabbay, D.M., Kruse, R., Nonnengart, A., Ohlbach, H.J. (eds) Qualitative and Quantitative Practical Reasoning. FAPR ECSQARU 1997 1997. Lecture Notes in Computer Science, vol 1244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035613
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DOI: https://doi.org/10.1007/BFb0035613
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