Incremental algorithms for attribute reduction in decision table
Guoyin Wang · Kongzhi yu juece · 2007
Incremental algorithms for attribute reduction based on modified discernibility matrix are proposed,by which minimal attribute reduction cluster of new decision table can be obtained quickly when new records are added to primary decision table.A distributed model of incremental attribute reduction is also presented by decomposing values of decision attribute of positive region and boundary region in non-tolerant decision table. The simulation experiments show the validity and effectiveness of algorithms.