Summary
The Rough Set Theory (RST) is a mathematical formalism for representing uncertainty, which can be considered an extension of the classical set theory. It has been used in many different research areas, including those related to inductive machine learning and reduction of knowledge in knowledge based systems. This chapter introduces the main concepts of the RST and presents a family of algorithms for implementing them.
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Uchôa, J.Q., do Carmo Nicoletti, M. (2004). An Algorithmic Approach to the Main Concepts of Rough Set Theory. In: Abraham, A., Jain, L., van der Zwaag, B.J. (eds) Innovations in Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39615-4_4
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DOI: https://doi.org/10.1007/978-3-540-39615-4_4
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