Title :
Research on an Optimized C4.5 Algorithm Based on Rough Set Theory
Author :
Xiang Zhuoyuan ; Zhang Lei
Author_Institution :
Sch. of Inf. & Safety Eng., Zhongnan Univ. of Econ. & Law, Wuhan, China
Abstract :
This paper proposes an improved algorithm based on the rough set theory and C4.5 decision tree. The algorithm uses rough set theory to reduce the attributes in the decision system, and uses the reduced data as the input of C4.5 algorithm to construct a decision tree. This article has put this new algorithm into practice, and the result of the experiment shows that the improved algorithm has higher efficiency and accuracy compared with the traditional C4.5 algorithm.
Keywords :
decision trees; rough set theory; C4.5 algorithm; C4.5 decision tree; rough set theory; Algorithm design and analysis; Classification algorithms; Data mining; Decision trees; Educational institutions; Set theory; Vegetation; C4.5; data mining; decision tree; reduce attributes; rough set;
Conference_Titel :
Management of e-Commerce and e-Government (ICMeCG), 2012 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2943-9
DOI :
10.1109/ICMeCG.2012.74
