摘要
决策树算法是数据挖掘中重要的分类算法。目前,已有许多构建决策树的算法,其中,ID3算法是核心算法。本文首先对ID3算法进行研究与分析,针对计算属性的信息熵十分复杂的缺点,提出了一种新的启发式算法SID3,它是基于属性对分类的敏感度的。文章最后通过实例对两种算法进行比较分析,结果表明,SID3算法能够生成正确的决策树,并且使建树过程更简便,更快速。
Decision tree is the most important classification algorithm in data mining.At present,there are many decision tree algorithms,ID3 algorithm is the core one.This paper first studies and analyses the ID3 algorithm,then discusses the complicacy of computing the Information Entropy of attribute,and put forward a new heuristic based on the sensitive of attribute contributing to the classification.Finally,this paper compares the two algorithms by experiments,the results show that SID3 can generate the correct decision tree and the process is more simple,more quickly.
出处
《计算机系统应用》
2010年第11期52-55,65,共5页
Computer Systems & Applications
