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An improved TANC classification algorithm based on C4.5
Zhao, Xiao-Qiang1; Yang, Jia-Min1,2
2014
会议日期May 31, 2014 - June 2, 2014
会议地点Changsha, China
关键词Classification (of information) Classifiers Forestry Learning systems Machine learning C4.5 algorithm Classification accuracy Classification algorithm Continuous data Data attributes Finite intervals Training data Tree augmented Naive Bayes
DOI10.1109/CCDC.2014.6853067
页码4992-4996
英文摘要Tree Augmented Naive Bayes Classification (TANC) 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 TANC. In this way it can improve the classification accuracy of the TANC. The experimental results show that the improved algorithm is superior to TANC in terms of classification accuracy. © 2014 IEEE.
会议录26th Chinese Control and Decision Conference, CCDC 2014
会议录出版者IEEE Computer Society
语种中文
内容类型会议论文
源URL[http://ir.lut.edu.cn/handle/2XXMBERH/117774]  
专题兰州理工大学
作者单位1.College of Electrical and Information Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China;
2.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050, China
推荐引用方式
GB/T 7714
Zhao, Xiao-Qiang,Yang, Jia-Min. An improved TANC classification algorithm based on C4.5[C]. 见:. Changsha, China. May 31, 2014 - June 2, 2014.
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