Abstract
Melanoma is a very serious and lethal skin cancer. In this paper six discretization algorithms, used for preprocessing of melanoma data, were compared using criteria of rule set complexity, total number of errors, and expert’s evaluation. The best discretization method was based on divisive clustering technique. An additional experiment in which the best rules from all six rule sets, selected by an expert, were used for melanoma prediction, was additionally conducted. Our conclusion is that in the original data set, cases with suspicious melanoma were not well represented.
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Bajcar, S., Grzymala-Busse, J.W., Hippe, Z.S. (2002). A Comparison of Six Discretization Algorithms Used for Prediction of Melanoma. In: Kłopotek, M.A., Wierzchoń, S.T., Michalewicz, M. (eds) Intelligent Information Systems 2002. Advances in Soft Computing, vol 17. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1777-5_1
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DOI: https://doi.org/10.1007/978-3-7908-1777-5_1
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