An incremental rule acquisition algorithm based on variable precision rough set model
Wang Guo-ying · Journal of Chongqing University of Posts and Telecommunications · 2005
In order to find a minimal set of rules for a decision table,the classical method cannot effectively deal with new instances added to the universe because of recalculation for the overall set of instance.In this paper,first,the relation of the new instances with the existing condition class,and effect on rule sets are studied when a new instance comes.Second,a new incremental learning algorithm based on variable precision rough set model is presented.Finally,the test results proves this algrothm feasible.