摘要
Rough Sets方法是一种处理不确定或模糊知识的重要工具 .本文在对 Rough Sets理论进行深入研究的基础上 ,提出了一种基于 Rough Sets的自增量学习算法 ,该算法利用简化的差异矩阵和置信度 。
The Rough set approach is an important tool to deal with uncertain or vague knowledge in AI applications. In this paper, the Rough set theory is deeply investigated, and an incremental learning algorithm based on Rough set theory is proposed. This algorithm can effectively produce deterministic rules or non deterministic rules using the simplified discernibility matrix and the confidence measurement.
出处
《小型微型计算机系统》
CSCD
北大核心
2001年第8期982-984,共3页
Journal of Chinese Computer Systems
关键词
粗糙集
自增长学习
差异矩阵
信息系统
规则学习
非确定性规则
人工智能
Rough sets
Incremental learning
Simplified discernibility matrix
Information system
Deterministic rules
Non deterministic rules
