Summary
In this chapter, a new rough set approach to decision making problems is proposed. It is assumed that the evaluations given by a decision maker are interval values. That is, we deal with the information system containing ambiguous decision expressed as interval values. By the approximations of the lower and upper bounds with respect to decision values, the approximations with interval decision values are illustrated in this chapter. The concept of the proposed approach resembles the one of Interval Regression Analysis. Furthermore, we discuss the unnecessary divisions between the decision values based on these bounds. The aim is to simplify IF-Then rules extracted from the information system. The method for removing the divisions is introduced using a numerical example.
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Sugihara, K., Tanaka, H. (2008). Rough Set Approach to Information Systems with Interval Decision Values in Evaluation Problems. In: Bello, R., Falcón, R., Pedrycz, W., Kacprzyk, J. (eds) Granular Computing: At the Junction of Rough Sets and Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol 224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76973-6_17
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DOI: https://doi.org/10.1007/978-3-540-76973-6_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76972-9
Online ISBN: 978-3-540-76973-6
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