An Effective Parallel Attribute Reduet Algorithm based on Relation Matrix

P.L. Zhou and C. Mingins (Australia)


Machine Learning, Rough Set, Reduct, Information System, Tolerance Relation Matrix, Tolerance, Knowledge Acquisition


In this paper, on the basis of studying the limitations of the basic rough set model, we present a Tolerance Information System that is based on a family set of tolerance relations between objects when given a set of tolerance relations. The model inherits most of the characteristics of the basic model of rough set; and they also have a better effect of approximation classification. Based on this model, we present a concept of relation matrix, and then propose a general parallel algorithm used in tolerance information systems; the parallel algorithm will give us a near-optimal attribute reduct, and we also discuss the dependency between attributes.

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