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Ordinal Decision Making with a Notion of Acceptable: Denoted Ordinal Scales

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Data Mining, Rough Sets and Granular Computing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 95))

Abstract

Our concern is with the problem of constructing decision functions to aid in making decision under uncertainty. We discuss the tradeoff that has to be made, when selecting a scale for representing our possible payoffs, between the power of the scale and the burden of the scale. We consider here the situation in which our basic scale is an ordinal scale, however we augment this scale by allowing an additional notion, a classification of payoffs as to whether they are acceptable or not. This allows us to have information such as A is preferred to B but both are acceptable. We indicate that this formally corresponds to an ordinal scale with a denoted element and call such a scale a Denoted Ordinal Scale (DOS). It is shown that this augmentation of the ordinal scale increases the power of the scale and therefore allows us to built more sophisticated decision models.

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© 2002 Springer-Verlag Berlin Heidelberg

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Yager, R.R. (2002). Ordinal Decision Making with a Notion of Acceptable: Denoted Ordinal Scales. In: Lin, T.Y., Yao, Y.Y., Zadeh, L.A. (eds) Data Mining, Rough Sets and Granular Computing. Studies in Fuzziness and Soft Computing, vol 95. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1791-1_19

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  • DOI: https://doi.org/10.1007/978-3-7908-1791-1_19

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2508-4

  • Online ISBN: 978-3-7908-1791-1

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