| 基于信息增益的缺省规则的挖掘方法 |
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| 引用本文： | 尹旭日,贾松茂. 基于信息增益的缺省规则的挖掘方法[J]. 计算机工程与应用, 2006, 42(6): 183-185 |
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| 作者姓名： | 尹旭日 贾松茂 |
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| 作者单位： | 中国人民解放军汽车管理学院基础部,蚌埠,233011 |
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| 摘 要： | Rough集方法是一种处理不确定或模糊知识的重要工具。论文在现有的基于Rough集理论的缺省规则挖掘算法的基础上,将单属性信息增益概念扩充为多属性的情况,提出了基于信息增益的缺省规则的搜索策略和挖掘方法。实验表明,该方法能够发现简洁、易理解和实用的规则,同时具有较低的计算复杂性。
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| 关 键 词： | 缺省规则 信息增益 Rough集 数据挖掘 |
| 文章编号： | 1002-8331-（2006）06-0183-03 |
| 收稿时间： | 2005-06-01 |
| 修稿时间： | 2005-06-01 |
Mining Default Rule Using Informtion Gain |
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| Yin Xuri,Jia Songmao. Mining Default Rule Using Informtion Gain[J]. Computer Engineering and Applications, 2006, 42(6): 183-185 |
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| Authors: | Yin Xuri Jia Songmao |
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| Affiliation: | Dept. of Basic Courses,Institute of Automobile Management of PLA,Bengbu 233011 |
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| Abstract: | The Rough set approach is an important tool to deal with uncertain or vague knowledge in AI applications. In this paper,the concept of multi-attribute information gain is introduced,then algorithms for mining default rules based on Rough set and information gain are proposed and applied to mine the default rule from the decision table. Experimental results show that this algorithm can effectively obtain concise,apprehensible and practicable default results. |
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| Keywords: | default rule information gain Rough set data mining |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
