A contribution to decision tree construction based on rough set theory

被引：0
|
作者：
Liu, XM [1 ]
Huang, HK
Xu, WX
机构：
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
[2] Capital Normal Univ, Sch Informat Engn, Beijing 100037, Peoples R China
[3] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
来源：
ROUGH SETS AND CURRENT TRENDS IN COMPUTING | 2004年 / 3066卷
关键词：
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：
In this paper, the algorithm of building a decision tree is introduced by comparing the information gain or entropy. The produced process of univariate decision tree is given as an example. According to rough sets theory, the method of constructing multivariate decision tree is discussed. Using the algorithm, the complexity of decision tree is decreased, the construction of decision tree is optimized and the rule of data mining could be built.
引用
收藏
页码：637 / 642
页数：6
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