基于不完备信息系统的Rough Set决策规则提取方法

An Approach to Extracting Rough Set Decision Rules Based on Imperfect Information Systems

对象信息的不完备性是从实例中归纳学习的最大障碍。针对不完备的信息,研究了基于不完备信息系统的粗糙集决策规则提取方法,利用分层递减约简算法,通过实例有效地分析和处理了含有缺省数据和不精确数据的信息系统,扩展了粗糙集的应用领域。

The incompleteness of information about objects may be the greatest obstacle to performing inductive learning from examples. This paper focuses on an approach to extracting rough set decision rules based on imperfect information systems when the information given is incomplete. IT effectively analyses and deals with information systems containing missing data and imprecise data by hierarchical reduction algorithm with instances. The approach extends applied categorizes of Rough set.