An Improved TANC Classification Algorith Based on C4.5

	An Improved TANC Classification Algorith Based on C4.5
	Zhao Xiao-qiang; Yang Jia-min
	2014
关键词	Machine learning classification C4.5 algorithm Tree Augmented Naive Bayes
页码	4992-4996
英文摘要	Tree Augmented Naive Bayes Classification (TANG) is not very well to deal with continuous data and it ignores partial data in the absence of data attribute value and this can reduce the result accuracy. To resolve this problem, an improved algorithm based on C4.5 is proposed in this paper. The proposed algorithm firstly modifies the available training data according to the predictions of C4.5, then continuous data is discretized by dividing many finite intervals of attributes, this modified training data is used to train TANG. In this way it can improve the classification accuracy of the TANG. The experimental results show that the improved algorithm is superior to TANG in terms of classification accuracy.
会议录	26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC)
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	中文
WOS研究方向	Automation & Control Systems
WOS记录号	WOS:000343577705033
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36671]
专题	电气工程与信息工程学院
通讯作者	Zhao Xiao-qiang
作者单位	Lanzhou Univ Tech, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Zhao Xiao-qiang,Yang Jia-min. An Improved TANC Classification Algorith Based on C4.5[C]. 见:.