Abstract
Data mining and knowledge discovery is described from pattern recognition point of view along with the relevance of soft computing. Key features of the computational theory of perceptions (CTP) and its significance in pattern recognition and knowledge discovery problems are explained. Role of fuzzy-granulation (f-granulation) in machine and human intelligence, and its modeling through rough-fuzzy integration are discussed. Merits of fuzzy granular computation, in terms of performance and computation time, for the task of case generation in large scale case based reasoning systems are illustrated through examples.
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Pal, S.K. (2006). Rough-Fuzzy Granular Computing, Case Based Reasoning and Data Mining. In: Di Gesú, V., Masulli, F., Petrosino, A. (eds) Fuzzy Logic and Applications. WILF 2003. Lecture Notes in Computer Science(), vol 2955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10983652_1
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DOI: https://doi.org/10.1007/10983652_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31019-8
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