| 基于粗糙集的数据挖掘属性约简算法研究 |
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| 引用本文： | 沈晨鸣. 基于粗糙集的数据挖掘属性约简算法研究[J]. 南京工程学院学报(自然科学版), 2007, 5(1): 30-34 |
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| 作者姓名： | 沈晨鸣 |
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| 作者单位： | 南京工程学院计算机工程学院,江苏,南京,211167 |
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| 基金项目： | 南京工程学院校科研和教改项目 |
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| 摘 要： | 粗糙集理论是一种研究不完整、不确定知识处理的数学工具,属性约简是粗糙集理论的核心内容之一.阐述了粗糙集理论的基本思想,给出了一种启发式的最小约简算法,通过一个实例,分析说明算法的可行性和有效性.
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| 关 键 词： | 粗糙集 数据挖掘 属性约简 |
| 文章编号： | 1672-2558（2007）01-0030-05 |
| 修稿时间： | 2006-06-052006-08-11 |
Research on Data Mining for Attribute Reduction Based on Rough Set Theory |
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| SHEN Chen-ming. Research on Data Mining for Attribute Reduction Based on Rough Set Theory[J]. Journal of Nanjing Institute of Technology :Natural Science Edition, 2007, 5(1): 30-34 |
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| Authors: | SHEN Chen-ming |
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| Affiliation: | School of Computer Engineering, Nanjing Institute of Technology, Nanjing 211167, China |
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| Abstract: | Rough set theory is a mathematical tool to study the processing of incomplete and uncertain knowledge, of which attribute reduction is one of the essential parts. This paper expounds the basic ideas of rough set theory and introduces illuminating algorithm for minimum reduction, Finally an example is given to testify the practicability and efficiency of the algorithm. |
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| Keywords: | Rough Set data mining attribute reduction |
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