Title :
A Decision Tree Algorithm Based on Dispersion Measure of Attribute Information
Author :
He Dengchao ; Hao Wenning ; Gan Wenyan ; Chen Gang ; Jin Dawei
Author_Institution :
Command Inf. Syst. Inst., PLA Univ. of Sci. &Technol., Nanjing, China
Abstract :
In this paper, an improved decision tree algorithm based on dispersion measure of attribute information was proposed, which combined information gain and dispersion of attribute information as an evaluation criterion of attribute selection in order to overcome the deficiency that ID3 decision tree algorithm leaned to the multi-value attribute. From results of the experiment, it can be demonstrated that the proposed algorithm could over the deficiency of leaning to the multi-value attribute, and has good performance on classification.
Keywords :
decision trees; pattern classification; ID3 decision tree algorithm; attribute information dispersion; attribute selection; classification; dispersion measure; evaluation criterion; information gain; multivalue attribute; Classification algorithms; Data mining; Decision trees; Dispersion; Gain measurement; Partitioning algorithms; Training; Decision Tree Algorithm; Dispersion Measure of Attribute Information; ID3; Information Gain;
Conference_Titel :
Web Information System and Application Conference (WISA), 2013 10th
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4799-3218-4
DOI :
10.1109/WISA.2013.25
