Data-driven decision tree learning algorithm based on rough set theory

被引：4
|
作者：
Yin, DS [1 ]
Wang, GY [1 ]
Wu, Y [1 ]
机构：
[1] Chongqing Univ Posts & Telecommun, Inst Comp Sci & Technol, Chongqing 400065, Peoples R China
来源：
PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON ACTIVE MEDIA TECHNOLOGY (AMT 2005) | 2005年
关键词：
rough set; data-driven; decision tree; pre-pruning;
D O I：
10.1109/AMT.2005.1505426
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Decision tree pre-pruning is an effective method to solve the over-fitting problem in decision tree learning process. However, it is difficult to estimate the exact time to stop the growing process of a decision tree, which limits the developments and applications of this method. In this paper, the growing of a decision tree is controlled by the uncertainty of a decision table, and a data-driven learning algorithm for decision tree prepruning is developed.
引用
收藏
页码：579 / 584
页数：6
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