A Complete Algorithm for Attribute Reduction Based on Dicernibility Matrix
Xiaowei Li
Abstract
Xiaowei Li
Abstract
To get a better set of attribute reduction,this paper proposed a new algorithm for attribute reduction based on the study of dicernibility matrix of rough sets.This algorithm focuses on the computing of the attribute set gotten from the dicernibility matrix,in order to get a new set.Based on the analysis of this new set,a complete algorithm for attribute reduction is given.Finally analyzed the time complexity of this algorithm and gave the proof of its completeness.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
To get a better set of attribute reduction,this paper proposed a new algorithm for attribute reduction based on the study of dicernibility matrix of rough sets.This algorithm focuses on the computing of the attribute set gotten from the dicernibility matrix,in order to get a new set.Based on the analysis of this new set,a complete algorithm for attribute reduction is given.Finally analyzed the time complexity of this algorithm and gave the proof of its completeness.
Key concepts: Computer science, Reduction (mathematics), Rough set, Attribute domain, Algorithm, Set (abstract data type), Completeness (order theory), Matrix (chemical analysis)