A Novel Algorithm for Classification Rule Discovery based on Concept Granule Structure
Zhao Jian, Leng Kong 
Journal of Digital Information Management, Vol. 14, No. 2, 2016.
DOI: 
Link: 
Abstract:
This study established concept elements
based on granular computing theory and the isomorphic
relation between rated scales in formal concept analysis
(FCA) and constructed the correlation of the concept elements.
A concept granule was constructed by studying
the mapping relation between concept elements. The common
polymerization and extension forms of the concept
granule were given. We studied the condition in which the
granular structure in a conceptual system is purified, as
well as the formation mechanism and generalized cohesiveness
of concept granules. An algorithm for classification
rule discovery algorithm based on concept granule
structure-the GRD algorithm-was created. According
to experimental results, the proposed GRD algorithm has
higher classification accuracy, simpler rule set, and better
generalization than traditional algorithms for classification
rule discovery. The formal representation based
on conceptual elements shows that a knowledge representation
model that is complete in terms of semantic
description can be built.