Learning directed probabilistic logical models: ordering-search versus structure-search
作者： Daan Fierens , Jan Ramon , Maurice Bruynooghe , Hendrik Blockeel
DOI: 10.1007/S10472-009-9134-9
关键词:
摘要: We discuss how to learn non-recursive directed probabilistic logical models from relational data. This problem has been tackled before by upgrading the structure-search algorithm initially proposed for Bayesian networks. In this paper we show upgrade another learning networks, namely ordering-search. For ordering-search was found work better than structure-search. It is non-obvious that these results carry over case, however, since there needs be implemented quite differently. Hence, perform an experimental comparison of upgraded algorithms on four domains. conclude also in case competitive with terms quality learned models, while significantly faster.
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sci-hub.se 参考文章(23)
J. W. Lloyd, Foundations of logic programming; (2nd extended ed.) Springer-Verlag New York, Inc.. ,(1987)
Lise Getoor, Nir Friedman, Avi Pfeffer, Daphne Koller, Ben Taskar, Method and apparatus for learning probabilistic relational models having attribute and link uncertainty and for performing selectivity estimation using probabilistic relational models ,(2001)
Kristian Kersting, Luc De Raedt, Basic principles of learning Bayesian logic programs inductive logic programming. pp. 189- 221 ,(2008) , 10.1007/978-3-540-78652-8_7
John Wylie Lloyd, Foundations of logic programming ,(1984)
Craig Boutilier, Nir Friedman, Daphne Koller, Moises Goldszmidt, Context-specific independence in Bayesian networks uncertainty in artificial intelligence. pp. 115- 123 ,(1996)
Learning equivalence classes of bayesian-network structures Journal of Machine Learning Research. ,vol. 2, pp. 445- 498 ,(2002) , 10.1162/153244302760200696
Daan Fierens, Learning directed probabilistic logical models from relational data Ai Communications. ,vol. 21, pp. 269- 270 ,(2008) , 10.3233/AIC-2008-0428
Nir Friedman, Moises Goldszmidt, Learning Bayesian networks with local structure uncertainty in artificial intelligence. pp. 252- 262 ,(1996) , 10.1007/978-94-011-5014-9_15
Kristian Kersting, Luc De Raedt, Towards Combining Inductive Logic Programming with Bayesian Networks inductive logic programming. ,vol. 2157, pp. 118- 131 ,(2001) , 10.1007/3-540-44797-0_10
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Generalized ordering-search for learning directed probabilistic logical models inductive logic programming. ,vol. 70, pp. 40- 42 ,(2007) , 10.1007/978-3-540-73847-3_10