一种两类决策系统的递增式粗集归纳学习方法  

AN INCREMENTAL ROUGH SET INDUCTIVE LEARNING APPROACH TO TWO CLASSES OF DECISION SYSTEMS

作　　者：王亚英[1] 邵惠鹤[1] 

机构地区：[1]上海交通大学自动化系,上海200030

出　　处：《信息与控制》2000年第6期521-525,共5页Information and Control

摘　　要：本文提出了一种两类决策系统的递增式粗集归纳方法 .首先利用基于粗集和用户要求的属性简化方法 ,对决策表进行属性简化 ;然后修改了决策矩阵和决策函数的定义 ,并采用基于修改后的决策矩阵和决策函数的方法从简化的决策表中归纳出决策规则 ;最后 ,一个例子验证了本文方法的有效性和实用性 .We present an incremental rough set inductive lea rn ing approach to two classes of decision systems. Firstly, based on rough set and user-require, we also propose an algorithm of feature reduction to reduce the decision table, such that a reduced decision table is generated. Secondly, w e modifies definitions of decision matrix and decision function and a method bas ed on modified decision matrix and decision function is introduced to produce th e decision rules from the reduced decision table. Finally, An example is also il lustrated in the paper, and proves that the approach is very effective.

关 键 词：粗集 决策表 决策矩阵 决策函数 归纳学习 决策规则 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]