Data mining: computational theory of perceptions and rough-fuzzy granular computing

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. New concept of rough-fuzzy clustering is introduced with algorithm. 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. Rough-fuzzy clustering is applied for segmenting brain MR images. Results show the superior performance in terms of β index.