Biomedical Engineering Reference
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12. R. Agrawal and R. Srikant, Fast Algorithms for Mining Association Rules, in Proceedings
of the 20th International Conference onVery Large Databases , Santiago, Chile, September,
1994.
13. A. Freitas, On rule interestingness measures, Knowledge-Based Syst. J. , 1999.
14. P.-N. Tan, V. Kumar, and J. Srivastava, Selecting the Right Interestingness Measure for
Association Patterns, in Proceedings of the Eight ACM SIGKDD Conference , Edmonton,
Canada, 2002.
15. R. Hilderman and H. Hamilton, Knowledge discovery and interestingness measures: a
survey, technical report cs 99-04, Technical report, Department of Computer Science,
University of Regina, October, 1999.
16. M. Khabzaoui, C. Dhaenens, A. N'Guessan, and E.-G. Talbi, Etude exploratoire des
critères de qualité des règies d'association en datamining, in Journées Françaises de
Statistique , 2003, pp. 583-587.
17. M. Khabzaoui, C. Dhaenens, and E.-G. Talbi, A Multicriteria Genetic Algorithm to Analyze
DNA Microarray Data, in Congress on Evolutionary Computation (CEC) , Vol II, Portland,
USA, IEEE Service center, June, 2004, pp. 1874-1881.
18. P. Smyth and R. M. Goodman, Rule Induction Using Information Theory, in
G. Piatetsky-Shapiro and J. Frawley, Knowledge Discovery in Databases , AAAI / MIT
Press, 1991, pp. 159-176.
19. K. Wang, S. H. W. Tay, and B. Liu, Interestingness-Based Interval Merger for Numeric
Association Rules, in R. Agrawal, P. E. Stolorz, and G. Piatetsky-Shapiro, Eds., in Proceed-
ings of Fourth International Conference Knowledge Discovery and Data Mining, KDD,
AAAI Press, New York, USA, 1998, pp. 121-128.
20. D. L. A. Araujo, H. S. Lopes, and A. A. Freitas, A Parallel Genetic Algorithm for Rule
Discovery in Large Databases, in Proceedings of 1999 IEEE Systems, Man and Cybernetics
Conference , Vol. III, Tokyo, Japan, October, 1999, pp. 940-945.
21. P. Kotala, P. Zhou, S. Mudivarthy, W. Perrizo, and E. Deckard, Gene Expression Pro-
filing of DNA Microarray Data Using Peano Count Trees, in Online Proceedings of
the First Virtual Conference on Genomics and Bioinformatics, URL: http://midas-
10.cs.ndsu.nodak.edu/bio/ , October, 2001.
22. D. E. Goldberg, Genetic Algorithms — in Search, Optimization and Machine Learning ,
Addison-Wesley Publishing Company, 1989.
23. L. Jourdan, C. Dhaenens, and E. G. Talbi, Rules Extraction in Linkage Disequilibrium
Mapping with an Adaptive Genetic Algorithm, in Proceedings of the European Conference
on Computational Biology (ECCB '03) , 2003, pp. 29-31.
24. T. P. Hong, H. Wang, and W. Chen, Simultaneously applying multiple mutation operators
in genetic algorithms, J. Heuristics , 6, 439-455 (2000).
25. C. M. Fonseca and P. J. Fleming, An overview of evolutionary algorithms in multiobjective
optimization, Evol. Comput. , 3 (1), 1-16 (1995).
26. D. A. van Veldhuizen and G. B. Lamont, On Measuring Multiobjective Evolutionary Algo-
rithm Performance, in In 2000 Congress on Evolutionary Computation , Piscataway, New
Jersey, Vol. 1, July, 2000, pp. 204-211.
27. A. Jaszkiewicz, On the performance of multiple objective genetic local search on the 0 / 1
knapsack problem, a comparative experiment, Technical report RA-002/2000, Institute of
Computing Science, Poznan University of Technology, Poznan, Poland, July, 2000.
28. J. D. Knowles, D. W. Corne, and M. J. Oates, On the Assessment of Multiobjective
Approaches to the Adaptive Distributed Database Management Problem, in Proceedings
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