Abstract
Rough sets can be interpreted in two ways: classification of objects and approximation of a set. In this paper, we discuss the differences and similarities of generalized rough sets based on those two different interpretations. We describe the relations between generalized rough sets and types of extracted decision rules. Moreover, we extend the discussion to fuzzy rough sets. Through this paper, the relations among generalized crisp rough sets and fuzzy rough sets are clarified and two different directions of applications in rule extraction are suggested.
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Inuiguchi, M. (2004). Generalizations of Rough Sets: From Crisp to Fuzzy Cases. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_3
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DOI: https://doi.org/10.1007/978-3-540-25929-9_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22117-3
Online ISBN: 978-3-540-25929-9
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