A Message Entropy Method of Learning from Examples

被引：0
|
作者：
刘占生
武新华
夏松波
机构：
来源：
Journal of Harbin Institute of Technology | 1997年 / 03期
关键词：
Machine learning; decision tree; extension matrix; message entropy; fault diagnosis;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Extension matrix（EM）and ID3 are two main algorithms with wide applicationin the field of machine learning,but analysis shows EM may Cause false diagnosis and ID3may cause fail diagnosis.This paper presents a new combination of these two methods toachieve a new method called entropy extension matrix（EEM）and a new concept ofgeneralization association ability（GAA）.Results show that this algorithm has propertiesbetter than those of EM and ID3.
引用
收藏
页码：10 / 13
页数：4
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