| 综合属性选择和删除的属性约简方法 |
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| 引用本文： | 杨成东杨成东1,邓廷权2. 综合属性选择和删除的属性约简方法[J]. 智能系统学报, 2013, 8(2): 183-186. DOI: 10.3969/j.issn.1673-4785.201209056 |
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| 作者姓名： | 杨成东杨成东1 邓廷权2 |
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| 作者单位： | 1.临沂大学 信息学院, 山东 临沂276005； 2.哈尔滨工程大学 理学院, 黑龙江 哈尔滨150001 |
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| 摘 要： | 属性约简能有效地消除信息冗余，广泛应用于人工智能、机器学习.通过实例指出基于辨识矩阵的经典的属性约简方法存在不能得到约简的可能性，仍具有冗余性.因此，提出了综合属性选择和删除算法的辨识矩阵属性约简方法，并有效解决该问题.通过UCI标准数据集验证表明，新方法比经典方法进一步减少了属性的个数，凸显其实用性和有效性.
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| 关 键 词： | 辨识矩阵 属性约简 信息冗余 人工智能 机器学习 属性选择 属性删除 |
An approach to attribute reduction combining attribute selection and deletion |
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| YANG Chengdong1,DENG Tingquan2. An approach to attribute reduction combining attribute selection and deletion[J]. CAAL Transactions on Intelligent Systems, 2013, 8(2): 183-186. DOI: 10.3969/j.issn.1673-4785.201209056 |
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| Authors: | YANG Chengdong1 DENG Tingquan2 |
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| Affiliation: | 1. School of Informatics, Linyi University, Linyi 276005, China; 2. College of Science, Harbin Engineering University, Harbin 150001, China |
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| Abstract: | Attribute reduction has been defined as a method for removing information redundancy effectively, which has been widely applied to artificial intelligence, and machine learning. However, an example demonstrates classical attribute reduction approaches based on discernibility matrix may not get a reduction with redundancy. Therefore, an attribute reduction based on discernibility matrix combining attribute selection and deletion was proposed and thus, the problem was solved effectively. Moreover, UCI standard data sets provide further explanations on the feasibility, effectiveness, and as well as additional information on reducing the number of attributes without the classical approaches. |
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| Keywords: | discernibility matrix attribute reduction information redundancy artificial intelligence machine learning attribute selection attribute deletion |
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