Yihong Cao
Chang Zhou University International Institute of Ubiquitous Computing, Jiangsu, Changzhou, 213164, China
Yuwan Gu
Chang Zhou University International Institute of Ubiquitous Computing, Jiangsu, Changzhou, 213164, China
Huanhuan Cai
Chang Zhou University International Institute of Ubiquitous Computing, Jiangsu, Changzhou, 213164, China
Yuqiang Sun
Chang Zhou University International Institute of Ubiquitous Computing, Jiangsu, Changzhou, 213164, China
ABSTRACT
The decision tree algorithm is the more popular areas of research in data mining and ID3 algorithm is the core algorithm of decision tree algorithm, through research and analysis of the ID3 algorithm, for its shortcoming of multi-value bias interrelated, difficult to remove noise and attribute is not close enough, this study presents attributes set dependence based on rough set theory, doing the attribute reduction considering properties interdependent, thereby removing redundant attributes and the algorithm of attribute set dependence is also given ,at the same time comparing complexity of the algorithm before and after improvement. The draw improved the algorithm is better than before.
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How to cite this article
Yihong Cao, Yuwan Gu, Huanhuan Cai and Yuqiang Sun, 2013. An Improved Decision Tree Algorithm Based on the Attribute Set Dependency. Information Technology Journal, 12: 6641-6645.
DOI: 10.3923/itj.2013.6641.6645
URL: https://scialert.net/abstract/?doi=itj.2013.6641.6645
DOI: 10.3923/itj.2013.6641.6645
URL: https://scialert.net/abstract/?doi=itj.2013.6641.6645