Some experimental results on learning probabilistic and possibilistic networks with different evaluation measures | Zendy

Christian Borgelt | Zendy; Rudolf Kruse | Zendy

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Some experimental results on learning probabilistic and possibilistic networks with different evaluation measures

Author(s) -

Christian Borgelt,

Rudolf Kruse

Publication year - 1997

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-63095-3

DOI - 10.1007/bfb0035613

Subject(s) - computer science , probabilistic logic , usable , inference , task (project management) , scheme (mathematics) , artificial intelligence , machine learning , mathematics , multimedia , systems engineering , mathematical analysis , engineering

A large part of recent research on probabilistic and possi- bilistic inference networks has been devoted to learning them from data. In this paper we discuss two search methods and several evaluation mea- sures 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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