摘要
基于粗集（ＲＳ）理论，针对知识表达系统提出一种新的归纳学习方法。对该方法中条件属性的简化，核值表的求取，决策规则的约简进行了详细讨论，并给出相应的求解算法。本方法为机器学习以及从数据库中进行机器发现提供了新的思路。
The paper proposed a new inductive learning approach to Knowledge Representation System based on Rough Set Theory. In the paper, we discuss on the reduction of conditional attributes, the acquisition of core table and the reduction of decision rules and then give a computing algorithm. The approach presents a new idea to machine learning and knowledge discovery from databases.
出处
《控制与决策》
EI
CSCD
北大核心
1999年第3期206-211,共6页
Control and Decision
基金
东南大学科学基金
关键词
知识表达系统
归纳学习
粗集理论
机器学习
rough set theory, knowledge representation system, decision table, inductive learning, decision rule
