Optimal Granularity Selection in Multi-granularity Decision Context Based on Evidence Theory
Multi-granularity formal concept analysis is an important tool for data mining and knowledge discovery.In this paper,we study the method of selecting the optimal granularity combination of attributes in multi-granularity formal decision context under covering multi-granularity.Firstly,based on the covering granularity method of attributes,multi-granularity formal context and multi-granularity formal decision context are defined,and rough approximation and belief structure in multi-granularity formal con-text are also defined.Secondly,based on granule consistency,the selection method of optimal granularity combination of attributes in granule consistent multi-granularity formal decision context is studied,and it is proved that the optimal granularity combination of attributes can be characterized by the belief function in evidence theory.Finally,based on rough set theory and evidence theory,the selection method of optimal granularity combination of attributes in granule consistent multi-granularity formal decision context is given.
formal concept analysismulti-granularityoptimal granularity selectionevidence theoryrough set
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