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二分查找判定树的RHC构造法

RHC construction method for binary search decision tree
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摘要 传统面向过程的二分查找判定树构造方法复杂且工作量大。通过分析二分查找判定树的特点,提出倾斜二叉树的定义和构造方法,并进行了相关性质的探究。利用逆向哈弗曼编码(Reversed Huffman Coding,RHC)和二分查找判定树的中序有序性,提出了一种面向计算的二分查找判定树构造法——RHC构造法。结合性能分析、对比,RHC构造法比传统面向过程的方法速度更快、效率更高。 The traditional process-oriented binary search decision tree construction method is complex and the workload is large. We analyze the features of the binary search decision tree,define the bias binary tree and put forward its construction method,as well as discuss the related properties. Based on the Reversed Huffman Coding RHC and the fact that the inorder traversal of binary search decision tree is ordered,this paper presents a computational-oriented method—RHC construction method—for constructing the binary search decision tree. Combined with performance analysis and comparison,RHC construction method is faster and more efficient than traditional process-oriented method.
作者 徐有为 张宏军 程恺 陈裕田 周彬彬 Hongjun;Cheng Kai;Chen Yutian;Zhou Binbin(System,Army Engineering University of PLA,Nanjing 210000,China)
出处 《信息技术与网络安全》 2018年第9期52-56,共5页 Information Technology and Network Security
基金 江苏省自然科学基金项目(BK20150720)
关键词 二分查找 判定树 倾斜二叉树 逆向哈夫曼编码 binary search decision tree bias binary tree reversed Huffman coding
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  • 1唐发明,王仲东,陈绵云.支持向量机多类分类算法研究[J].控制与决策,2005,20(7):746-749. 被引量:90
  • 2孟媛媛,刘希玉.一种新的基于二叉树的SVM多类分类方法[J].计算机应用,2005,25(11):2653-2654. 被引量:42
  • 3谭明锋,高蕾,龚正虎.IP路由查找算法研究概述[J].计算机工程与科学,2006,28(6):77-80. 被引量:14
  • 4孙茂松,黄昌宁,邹嘉彦,陆方,沈达阳.利用汉字二元语法关系解决汉语自动分词中的交集型歧义[J].计算机研究与发展,1997,34(5):332-339. 被引量:66
  • 5Vapoik V N.Statistical learning theory[M].Beijing:PHEI,2009.
  • 6Cristianini N.An introduction to support vector machines[M].Beijing:China Machine Press,2004.
  • 7Bottou L,Cortes C,Denker J.Comparison of classifier methods:A case study in handwriting digit recognition[C] //Proceedings of International Conference on Pattern Recognition,1994:77-87.
  • 8Krelel U.Pairwise classification and support vector machines[M].Cambridge,MIA:MIT Press,1999:255-268.
  • 9Platt J C,Cristianini N,Shawe-taylor J.Large margin DAGs for multiclass classification[C] //Advances in Neural Information Processing Systems.Cambridge,MA:MIT Press,2000:547-553.
  • 10Melgani F,Bruzzone L.Classification of hyperspectral remote sonsing images with support vector machines[J].IEEE Transactions on Geosciences and Remote Sensing,2004,42(8):1778-1790.

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