| 基于区分矩阵的属性约简算法改进策略 |
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| 引用本文： | 王慧,王京,张彩云.基于区分矩阵的属性约简算法改进策略[J].武汉冶金科技大学学报,2011(2):126-130. |
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| 作者姓名： | 王慧 王京 张彩云 |
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| 作者单位： | [1]北京科技大学信息工程学院,北京100083 [2]中国人民公安大学信息安全工程系,北京100038 |
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| 基金项目： | 国家高技术研究发展计划（863计划）资助课题（2009AA04Z136） |
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| 摘 要： | 针对大容量数据表构造的区分矩阵过于庞大致使属性约简算法效率低的问题,引入置信度和支持度,提取大型数据库中的高概率事件,重新构造决策数据表,并在构造区分矩阵过程中剔除重复项和包含项,结果使得比较次数减少、存储空间节省、约简效率提高。
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| 关 键 词： | 决策表 区分矩阵 属性频度 属性约简 |
Improvement of attribute reduction algorithm based on discernibility matrix |
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| Authors: | Wang Hui Wang Jing Zhang Caiyun |
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| Affiliation: | 1.School of Information Engineering,University of Science and Technology Beijing,Beijing 100083,China; 2.Department of Information Security,Chinese People＇s Public Security University,Beijing 100038,China) |
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| Abstract: | In knowledge system of large database,large discernibility matrix reduces efficiency of attribute reduction algorithm.To solve this problem,confidence and support are introduced to reconstruct the decision table by extracting high probability events of a large database.In the reduction algorithm based on discernibility matrix attribute,the duplicates and contains items are removed to reduce comparison times.As a result,the efficiency of attribute reduction algorithm is improved and the storage space is saved. |
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| Keywords: | decision table discernibility matrix attribute frequency attribute reduction |
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