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Many theories are developed based on probability to deal with incomplete information. The fuzzy logic deals with belief rather than likelihood (probability). Zadeh first defined fuzzy set as a single membership function. The two fold fuzzy sets with two membership functions will give more evidence than a single membership one. Therefore there is need of fuzzy logic with two membership functions. In...
the logical data independence and physical data independence are necessary for data mining particularly for BIG DATA. The data base defining inherency with fuzziness will reduce the time in Information retrieval. The Data Mining is very fast using the fuzzy log for BIG DATA. In this paper, fuzzy data mining is studied and fuzzy association dependency is defied. The fuzzy MapReducibg algorithm is studied...
Knowledge representation is key factor for problem representation particularly for incomplete information in expert systems. Usually incomplete information is fuzzy rather than likelihood. Learning methods are necessary to solve expert problems. The conditional inference method is studied different from Zadeh, Mamdani and TSK methods. Learning fuzzy conditional inference with individual methods fuzzy...
Zadeh, Mamdani, TSK and Fukami are proposed different fuzzy conditional inferences. Mamdani is also proposed for nested fuzzy conditional inference. In this paper, some methods on fuzzy conditional inference and fuzzy reasoning are studied to approximate reasoning. The Business Intelligence and Medical diagnosis are given as an example.
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