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An Empirical Evaluation of Bagging in Inductive Logic Programming (2002)  (Make Corrections)  (9 citations)
Inês de Castro Dutra, David Page, Vítor Santos Costa, Jude Shavlik



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Abstract: Ensembles have proven useful for a variety of applications, with a variety of machine learning approaches. While Quinlan has applied boosting to FOIL, the widely-used approach of bagging has never been employed in ILP. Bagging has the advantage over boosting that the different members of the ensemble can be learned and used in parallel. (Update)

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Relational Data Mining with Inductive Logic . . . - Mooney (2004)   (Correct)

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BibTeX entry:   (Update)

I. de Castro Dutra, D. Page, V. Santos Costa, and J. Shavlik. An empirical evaluation of bagging in inductive logic programming. In Proceedings of the Twelfth International Conference on Inductive Logic Programming, Sydney, Australia, July 2002. Springer-Verlag. http://citeseer.ist.psu.edu/article/decastrodutra02empirical.html   More

@misc{ dutra02empirical,
  author = "I. Dutra and D. Page and V. Costa and J. Shavlik",
  title = "An empirical evaluation of bagging in inductive logic programming",
  text = "I. de Castro Dutra, D. Page, V. Santos Costa, and J. Shavlik. An empirical
    evaluation of bagging in inductive logic programming. In Proceedings of
    the Twelfth International Conference on Inductive Logic Programming, Sydney,
    Australia, July 2002. Springer-Verlag.",
  year = "2002",
  url = "citeseer.ist.psu.edu/article/decastrodutra02empirical.html" }
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52   Popular ensemble methods: An empirical study - Opitz, Maclin - 1999
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7   Parallel inductive logic programming - Dehaspe, De Raedt - 1995
4   Receiver-operative characteristic (context) - Zweig, Campbell - 1993
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3   Parallel inductive logic programming (context) - Graham, Page et al. - 2000
3   The application of ILP to finite element mesh design (context) - Dolak, Muggleton - 1991
2   Parallel induction algorithms for large samples - Matsui, Inuzuka et al. - 1998
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