| 一种基于成对约束的特征选择改进算法 |
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| 引用本文： | 杨杨,刘会东.一种基于成对约束的特征选择改进算法[J].南京师范大学学报,2011,11(1). |
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| 作者姓名： | 杨杨 刘会东 |
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| 作者单位： | 杨杨,Yang Yang(南京师范大学强化培养学院,江苏南京,210046);刘会东,Liu Huidong(南京师范大学计算机科学与技术学院,江苏南京,210046) |
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| 基金项目： | 南京师范大学2010年学生科学基金 |
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| 摘 要： | 基于成对约束的特征选择算法通过度量单个特征的重要性得到一个特征序列,但由单个重要特征构成的特征子集未必是最有效的.为此,提出了一种基于成对约束的特征选择改进算法,该算法采用对特征子集进行度量的策略,逐步选择使新的特征子集最有效的特征,从而得到一个有效的特征序列.实验表明新提出的算法是有效可行的.
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| 关 键 词： | 机器学习 特征选择 成对约束 分类 |
An Improved Algorithm for Feature Selection Based on Pairwise Constraint |
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| Yang Yang,Liu Huidong.An Improved Algorithm for Feature Selection Based on Pairwise Constraint[J].Journal of Nanjing Nor Univ: Eng and Technol,2011,11(1). |
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| Authors: | Yang Yang Liu Huidong |
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| Affiliation: | Yang Yang1,Liu Huidong2 (1.Intensification Culture School,Nanjing Normal University,Nanjing 210046,China,2.School of Computer Science and Technology,China) |
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| Abstract: | Feature selection is key issue in machine learning field.As compared with unsupervised feature selection methods,supervised feature selection approaches have more better performances.However,most of the existing supervised feature selection algorithms mainly aim at the cases using the labels as supervised information,here these methods are not applied to the cases with pairwise constraints.In the real application,it is more easier to get the pairwise constraints as comparing with getting labels.So the resea... |
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| Keywords: | machine learning feature selection pairwise constraint classification |
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