| 一种基于属性敏感度的决策树算法 |
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| 引用本文： | 王梅,于京,刘光.一种基于属性敏感度的决策树算法[J].计算机系统应用,2010,19(11):52-55. |
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| 作者姓名： | 王梅 于京 刘光 |
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| 作者单位： | 1. 北京电子科技职业学院科技工程学院电子工程系,北京市,100016
2. 北京市电信工程设计院有限公司,北京市,100036 |
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| 摘 要： | 决策树算法是数据挖掘中重要的分类算法。目前,已有许多构建决策树的算法,其中,ID3算法是核心算法。本文首先对ID3算法进行研究与分析,针对计算属性的信息熵十分复杂的缺点,提出了一种新的启发式算法SID3,它是基于属性对分类的敏感度的。文章最后通过实例对两种算法进行比较分析,结果表明,SID3算法能够生成正确的决策树,并且使建树过程更简便,更快速。
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| 关 键 词： | 数据挖掘 决策树 分类 ID3算法 属性敏感度 |
| 收稿时间： | 3/8/2010 12:00:00 AM |
| 修稿时间： | 2010/4/23 0:00:00 |
Sensitive Attribute Algorithm for Decision Tree SID3 |
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| WANG Mei,YU Jing,LIU Guang.Sensitive Attribute Algorithm for Decision Tree SID3[J].Computer Systems& Applications,2010,19(11):52-55. |
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| Authors: | WANG Mei YU Jing LIU Guang |
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| Affiliation: | 1.Dept.of Electronic Engineering,Institute of Science and Technology Engineering,Beiing Electronic Science and Technology Vocational College,Beijing 100016,China;2.Beijing Telecom Engineering Design Institute Co,Ltd.,Beijing 100036,China) |
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| Abstract: | Decision tree is the most important classification algorithm in data mining. At present, there are many decision tree algorithms, ID3 algorithm is the core one. This paper first studies and analyses the ID3 algorithm, then discusses the complicacy of computing the Information Entropy of attribute, and put forward a new heuristic based on the sensitive of attribute contributing to the classification. Finally, this paper compares the two algorithms by experiments, the results show that SID3 can generate the correct decision tree and the process is more simple, more quickly. |
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| Keywords: | decision tree ID3 algorithm sensitive of attribute |
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