Information Technology Reference
In-Depth Information
18. Montani, S., Portinale, L., Leonardi, G., Bellazzi, R., Bellazzi, R.: Case-based retrieval
to support the treatment of end stage renal failure patients. Artificial Intelligence in
Medicine 37(1), 31-42 (2006)
19. Nersessian, N.: The cognitive basis of model-based reasoning in science. In: The Cognitive
Basis of Science, ch. 7, pp. 133-153. Cambridge University Press, Cambridge (2002)
20. Olsson, E., Funk, P., Xiong, N.: Fault diagnosis in industry using sensor readings and case-
based reasoning. Journal of Intelligent and Fuzzy Systems 15(1), 41-46 (2004)
21. Pan, R., Yang, Q., Pan, S.J.: Mining competent case bases for case-based reasoning. Artifi-
cial Intelligence 171, 1039-1068 (2007)
22. Ritter, G.L., Woodruff, H.B., Lowry, S.R., Isenhour, T.L.: Algorithm for a selective nearest
neighbor decision rule. IEEE Transactions on Information Theory 21, 665-669 (1975)
23. Smyth, B., Keane, M.T.: Remembering to forget - A competence-preserving case dele-
tion policy for case-based reasoning systems. In: Proceedings of the Fourteenth Interna-
tional Joint Conference on Artificial Intelligence, IJCAI 1995), August 20-25, vol. 1 and 2,
pp. 377-382 (1995)
24. Smyth, B., McKenna, E.: Modelling the competence of case-bases. In: Smyth, B., Cunning-
ham, P. (eds.) EWCBR 1998. LNCS (LNAI), vol. 1488, pp. 208-220. Springer, Heidelberg
(1998)
25. Smyth, B., McKenna, E.: Building compact competent case-bases. In: Althoff, K.-D.,
Bergmann, R., Branting, L.K. (eds.) ICCBR 1999. LNCS (LNAI), vol. 1650, pp. 329-342.
Springer, Heidelberg (1999)
26. Smyth, B., McKenna, E.: Competence models and the maintenance problem. Computa-
tional Intelligence 17, 235-249 (2001)
27. Tomek, I.: An experiment with the edited nearest-neighbor rule. IEEE Transactions On
Systems Man and Cybernetics 6, 448-452 (1976)
28. Watson, I.: Case-based reasoning is a methodology not a technology. Knowledge-Based
Systems 12, 303-308 (1999)
29. Wilson, D.L.: Asymptotic properties of nearest neighbor rules using edited data. IEEE
Transactions On Systems Man and Cybernetics SMC 2, 408-420 (1972)
30. Wilson, D.R., Martinez, T.R.: Instance pruning techniques. In: Machine Learning: Proceed-
ings of the Fourteenth International Conference (ICML 1997), pp. 404-411. Morgan Kauf-
mann, San Francisco (1997)
31. Wilson, D.R., Martinez, T.R.: Reduction techniques for instance-based learning algorithms.
Machine Learning 38, 257-286 (2000)
32. Winston, P.H.: Learning and reasoning by analogy. Commun. ACM 23, 689-703 (1980)
33. Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the strength pareto evolutionary
algorithm for multiobjective optimization. In: Evolutionary Methods for Design Optimiza-
tion and Control with Applications to Industrial Problems, Athens, Greece, pp. 95-100.
International Center for Numerical Methods in Engineering (2001)
Search WWH ::
Custom Search