TY - JOUR
T1 - A New Reduction Implementation Based on Concept
AU - 
JO - Journal of Information and Computing Science
VL - 3
SP - 223
EP - 227
PY - 2024
DA - 2024/01
SN - 2
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22802.html
KW - rough set, reduction, pruning, backward elimination 

AB -  Rough set is one of the most useful data mining techniques. How to use rough set to extract rule 
is the basement of rough set’s application. This paper discuss an algorithm that be used in attribute reduction.  
To attribute reduction, generally method is based on discernibility matrix or its improvement. But this series 
methods  usually  get  one  reduction,  can’t  accommodate  uncertain  information  reasoning.  We  provide  a 
reduction algorithm, which based on reduction pruning. It can calculate all reductions, and suits any uncertain 
knowledge  reasoning.  For  increase  this  algorithm’s  effective,  we  present  two  theorems  to  make  algorithm 
simplified.  We  calculate  reduction  through  rough  reduction  (reduction  pruning)  and  backward  elimination 
two steps. The case illustrates we get the reduction effectively through this algorithm.