1BC2: A true first-order Bayesian classifier

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2583, Issue , 2003, Pages 133-148

  Lachiche, Nicolas ^a   Flach, Peter A ^b  

^a UNIVERSITÉ DE STRASBOURG   (France)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTERS;

BAYESIAN CLASSIFIER; FIRST ORDER; GIVEN FEATURES; PARAMETRIC DISTRIBUTIONS; PRE-PROCESSING STEP; STRUCTURED DATA;

INDUCTIVE LOGIC PROGRAMMING (ILP);

EID: 7044220231     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-36468-4_9     Document Type: Conference Paper

References (10)

1. H. Boström and L. Asker. Combining divide-and-conquer and separate-and-conquer for efficient and effective rule induction. In S. Džeroski and P. Flach, editors, Proceedings of the 9th InternationalWorkshop on Inductive Logic Programming, volume 1634 of Lecture Notes in Artificial Intelligence, pages 33-43. Springer-Verlag, 1999.
2. Sašo Džeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck, and Hendrik Blockeel. Diterpene structure elucidation from 13c nmr spectra with inductive logic programming. Applied Artificial Intelligence, 12(5):363-383, July- August 1998. Special Issue on First-Order Knowledge Discovery in Databases.
3. P. Flach and N. Lachiche. 1BC:A first-order Bayesian classifier. In S. Džeroski and P. Flach, editors, Proceedings of the 9th International Workshop on Inductive Logic Programming, volume 1634 of Lecture Notes in Artificial Intelligence, pages 92-103. Springer-Verlag, 1999.
4. Jerome H. Friedman. On bias, variance, 0/1-loss, and the curse-of-dimensionality. Data Mining and Knowledge Discovery, 1(1):55-77, March 1997.
5. Thomas Gärtner and Peter Flach. A linear kernel on strongly typed terms. In Multi-Relational Data Mining workshop, Joint workshop of ECML'01 and PKDD'01, 2001.
6. Nicolas Lachiche and Peter A. Flach. A first-order representation for knowledge discovery and bayesian classification on relational data. In Pavel Brazdil and Alipio Jorge, editors, Data Mining, decision Support, Meta-learning and ILP : Forum for Practical Problem Presentation and Prospective Solutions (DDMI-2000), Workshop of 4th International Conference on Principles of Data Mining and Knowledge Discovery (PKDD-2000), pages 49-60, Lyon, September 2000.
7. N. Lavrač, S. Džeroski, and M. Grobelnik. Learning nonrecursive definitions of relations with LINUS. In Y. Kodratoff, editor, Proceedings of the 5th European Working Session on Learning, volume 482 of Lecture Notes in Artificial Intelligence, pages 265-281. Springer- Verlag, 1991.
8. S. Muggleton, A. Srinivasan, R. King, and M. Sternberg. Biochemical knowledge discovery using Inductive Logic Programming. In H. Motoda, editor, Proceedings of the first Conference on Discovery Science, Berlin, 1998. Springer-Verlag.
9. U. Pompe and I. Kononenko. Naive Bayesian classifier within ILP-R. In L. De Raedt, editor, Proceedings of the 5th InternationalWorkshop on Inductive Logic Programming, pages 417- 436. Department of Computer Science, Katholieke Universiteit Leuven, 1995.
10. A. Srinivasan, S. Muggleton, R.D. King, and M.J.E. Sternberg. Mutagenesis: ILP experiments in a non-determinate biological domain. In S. Wrobel, editor, Proceedings of the 4th International Workshop on Inductive Logic Programming, volume 237 of GMD-Studien, pages 217-232. Gesellschaft für Mathematik und Datenverarbeitung MBH, 1994.