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Sensitivity of Rough Classification to Changes in Norms of Attributes

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Part of the book series: Theory and Decision Library ((TDLD,volume 11))

Abstract

Rough classification of patients after highly selective vagotomy (HSV) for duodenal ulcer is analysed from the viewpoint of sensitivity of previously obtained results to minor changes in the norms of attributes. The norms translate exact values of pre-operating quantitative attributes into 2 to 4 qualitative terms, e.g. “low”, “medium” and “high”. An extensive computational experiment leads to the general conclusion that original norms following from medical experience were well defined, and that the results of analysis of the considered information system using rough sets theory are robust in the sense of low sensitivity to minor changes in the norms of attributes.

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References

  1. Boryczka, M., Slowinski, R. (1988). Derivation of optimal decision algorithms from decision tables using rough sets. Bull. Polish Acad. Sci., Tech. Sci., 36 (3–4), 251–260.

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© 1992 Springer Science+Business Media Dordrecht

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Słowiński, K., Słowiński, R. (1992). Sensitivity of Rough Classification to Changes in Norms of Attributes. 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_22

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  • DOI: https://doi.org/10.1007/978-94-015-7975-9_22

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4194-4

  • Online ISBN: 978-94-015-7975-9

  • eBook Packages: Springer Book Archive

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