The Choquet-integral as an aggregation operator in case-based learning

Advances in Soft Computing

Volumn 38, Issue , 2006, Pages 615-627

  Hüllermeier, Eyke ^a  

^a NONE

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EID: 79959213005     PISSN: 16153871     EISSN: 18600794     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (19)

1. D.W. Aha, editor. Lazy Learning. Kluwer, Dordecht, 1997
2. D.W. Aha, D. Kibler, and M.K. Albert. Instance-based learning algorithms. Machine Learning, 6(1):37-66, 1991 (Pubitemid 21727227)
3. G. Choquet. Theory of capacities. Annales de l'Institut Fourier, 5:131-295, 1954
4. B.V. Dasarathy, editor. Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques IEEE Computer Society Press, Los Alamitos, California, 1991
5. S.A. Dudani. The distance-weighted k-nearest-neighbor rule. IEEE Transactions on Systems, Man, and Cybernetics, SMC-6(4):325-327, 1976
6. J. Fodor and M. Roubens. Fuzzy Preference Modelling and Multicriteria Decision Support. Kluwer, Dordrecht, The Netherlands, 1994
7. M. Grabisch. Fuzzy integral for classification and feature extraction. In M. Grabisch, T. Murofushi, and M. Sugeno, editors, Fuzzy Measures and Integrals: Theory and Applications, pages 415-434. Physica-Verlag, Wurzburg, 2000
8. E. Hüllermeier. On the representation and combination of evidence in instancebased learning. In Proc. ECAI-2002, pages 360-364, Lyon, France, 2002. IOS Press
9. E. Hüllermeier. Cho-k-NN: A method for combining interacting pieces of evidence in case-based learning. In Proc. IJCAI-05, pages 3-8, Edinburgh, Scotland, 2005
10. J.L. Kolodner. Case-based Reasoning. Morgan Kaufmann, San Mateo, 1993
11. M. Lindenbaum, S. Marcovich, and D. Rusakov. Selective sampling for nearest neighbor classifiers. In Proceedings AAAI-99, 16th National Conference on Artificial Intelligence, pages 366-371, Orlando, Florida, 1999
12. M.A. Oliver and R. Webster. Kriging: a method of interpolation for geographical information system. Internation Journal of Geographical Information Systems, 4(3):313-332, 1990
13. M.M. Richter. On the notion of similarity in case-based reasoning. In G. Della Riccia et al., editor, Mathematical and Statistical Methods in Artificial Intelligence, pages 171-184. Springer Berlin Heidelberg New York, 1995
14. C.K. Riesbeck and R.C. Schank. Inside Case-based Reasoning. Hillsdale, New York, 1989
15. R.E. Schapire, Y. Freund, P. Bartlett, and W.S. Lee. Boosting the margin: a new explanation for the evectiveness of voting methods. Annals of Statistics, 26:1651-1686, 1998 (Pubitemid 128376902)
16. M. Sugeno. Theory of Fuzzy Integrals and its Application. PhD thesis, Tokyo Institute of Technology, 1974
17. D. Wettschereck, D.W. Aha, and T. Mohri. A review and empirical comparison of feature weighting methods for a class of lazy learning algorithms. AI Review, 11:273-314, 1997 (Pubitemid 127508242)
18. R.R. Yager. Soft aggregation methods in case based reasoning. Applied Intelligence, 21:277-288, 2004
19. J. Zhang, Y. Yim, and J. Yang. Intelligent selection of instances for prediction in lazy learning algorithms. Artificial Intelligence Review, 11:175-191, 1997 (Pubitemid 127508238)