[1]孙林 徐久成 马媛媛.基于决策熵的决策树规则提取方法[J].计算机技术与发展,2007,(06):97-100.
　SUN Lin,XU Jiu-cheng,MA Yuan-yuan.Algorithm for Rules Extraction of Decision Tree Based on Decision Information Entropy[J].,2007,(06):97-100.
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基于决策熵的决策树规则提取方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2007年06期
页码:
97-100
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Algorithm for Rules Extraction of Decision Tree Based on Decision Information Entropy
文章编号:
1673-629X（2007）06-0097-04
作者:
孙林 徐久成 马媛媛
河南师范大学计算机与信息技术学院
Author(s):
SUN Lin;  XU Jiu-cheng;  MA Yuan-yuan
College of Computer ＆ Information Technology, Henan Normal University
关键词:
粗糙集; 决策熵; 决策树; 决策规则
Keywords:
rough set ; decision information entropy;  decision tree;  decision rules
分类号:
TP18
文献标志码:
A
摘要:
在决策表中,决策规则的可信度和对象覆盖度是衡量决策能力的重要指标。以知识粗糙熵为基础,提出决策熵的概念,并定义其属性重要性;然后以条件属性子集的决策熵来度量其对决策分类的重要性,自顶向下递归构造决策树;最后遍历决策树,简化所获得的决策规则。该方法的优点在于构造决策树及提取规则前不进行属性约简,计算直观,时间复杂度较低。实例分析的结果表明,该方法能获得更为简化有效的决策规则
Abstract:
In decision table, the reliability and objects coverage of decision rules are the most important performance metric for estimating decision ability. Based on rough entropy of knowledge, a new decision information entropy is proposed. The new significance of an attribute is defined, which is based on this entropy. In the process of constructing decision tree, condition attributes are considered to estimate the significance for decision classes. A procedure for reduction of traversing decision rules is also constructed, and helps to get more precise rules. The benefit of the method is that it needn＇t attribute reduction before extracting decision rules, and its computation is simple and intuitionistic. The experiment and comparison show that the algorithm provides more precise and simple decision rules

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备注/Memo

备注/Memo:
河南省自然科学基金项目（0511011500）;河南省高校新世纪优秀人才支持计划（2006HANCET-19）孙林（1979-）,男,河南南阳人,硕士研究生,研究方向为粗糙集理论、数据挖掘; 徐久成,教授,研究方向为粗糙集理论、粒计算、数据挖掘等
更新日期/Last Update: 1900-01-01