A Comparison of Six Discretization Algorithms Used for Prediction of Melanoma

Author:

Bajcar Stanislaw,Grzymala-Busse Jerzy W.,Hippe Zdzislaw S.

Publisher

Physica-Verlag HD

Reference16 articles.

1. Bajcar, S. and Hippe, Z. S.: Risk estimate of melanoma diagnosis on the basis of assessment of dermatoscopic patterns. Proc. of the National Conference Telemedycyna, Lodz, Poland, August 17–19, 1999, 175–178.

2. Booker, L. B., Goldberg, D. E., and Holland, J. F.: Classifier systems and genetic algorithms. In Machine Learning. Paradigms and Methods. Carbonell, J. G. (Ed.), The MIT Press, Boston, MA, 1990, 235–282.

3. Chmielewski, M. R. and Grzymala-Busse, J. W.: Global discretization of continuous attributes as preprocessing for machine learning. Int. Journal of Approximate Reasoning 15 (1996) 319–331.

4. Friedman, R. J. Rigel, D. S., and Kopf, A. W.: Early detection of malignant melanoma: the role of physician examination and self-examination of the skin. CA Cancer J. Clin. 35 (1985) 130–151.

5. Grzymala-Busse, J. P., Grzymala-Busse, J. W., and Hippe, Z. S.: Melanoma prediction using data mining system LERS. Proc. of the 25th Anniversary Annual International Computer Software and Applications Conference COMPSAC 2001, Oct. 8–12, 2001, Chicago, IL, 615–620.

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