Granular Computing on Natural Intervals Partition of Attribute Values in Decision Systems

A simple and more concrete granular computing model may be developed using partition of interval set-valued in decision System. The natural intervals of attribute values to be transformed into multiple sub-interval of [0, 1] are given by normalization. And some characteristics of interval set-valued of decision systems in fuzzy rough set theory are discussed. The correctness and effectiveness of the approach are shown in experiments. The approach presented in this paper can also be used as a data preprocessing step for other symbolic knowledge discovery or machine learning methods other than rough set theory.

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