Abstract
In statistics, classical discriminant analysis methods explain a predefined classification of a set of objects, by using the discrete values taken by these objects on some conditional attributes. Rough sets theory has the same objective. The purpose of the paper is to describe some experiments made to compare both approaches. In a first section, we recall the results obtained by Wong et al. for the comparison of rough sets theory with the Quinlan’s method, using the notion of entropy. Section two is devoted to a comparison of rough sets approach with a specific discriminant method, the Elysee method; an application is solved by both methods and similar results are obtained. In the last section, we analyse a real case study concerning a production problem, in a printing company, by both methodologies.
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References
Benjelloun M., Problème de production dans une imprimerie, Travail de fin d’études, Faculté Polytechnique de Mons (1989).
Ellard C. et al., Programme Elysee: présentation et application, Revue Metra, (1967) 503–520.
Lebart L. et al., Techniques de la description statistique; méthodes et logiciels pour l’analyse des grands tableaux, Dunod (1977).
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Slowinski R.; Stefanowski J., RoughDas and RoughClass software implementations of the rough sets approach, Chapter I11.8 in this volume (1992).
Wong et al., Comparison of rough sets and statistical methods in inductive learning, Int. J. Man-Machines studies, 24 (1986) 53–72.
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© 1992 Springer Science+Business Media Dordrecht
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Teghem, J., Benjelloun, M. (1992). Some Experiments to Compare Rough Sets Theory and Ordinal Statistical Methods. In: Słowiński, R. (eds) Intelligent Decision Support. Theory and Decision Library, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7975-9_17
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DOI: https://doi.org/10.1007/978-94-015-7975-9_17
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4194-4
Online ISBN: 978-94-015-7975-9
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