| 用于分类的样本保局鉴别分析方法 |
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| 引用本文： | 杨利平,辜小花,叶洪伟. 用于分类的样本保局鉴别分析方法[J]. 光学精密工程, 2011, 19(9): 2205-2213. DOI: 10.3788/OPE.20111909.2205 |
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| 作者姓名： | 杨利平 辜小花 叶洪伟 |
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| 作者单位： | 重庆大学光电技术及系统教育部重点实验室,重庆,400044 |
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| 基金项目： | 中央高校基本科研业务费科研专项项目(No.CDJZR10120010); 高等学校博士学科点专项科研基金资助项目(No.20100191120012) |
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| 摘 要： | 针对高维数据分类中鉴别特征降维方法的小样本问题和有效维度丢失问题,结合最新提出的片对齐框架和保局投影提出了样本保局鉴别分析方法.该方法通过分别构造每个样本的类内近邻图和类外近邻图,并将所有样本的类内近邻图和类外近邻图结合起来,形成了所有样本的类内近邻和类外近邻关系.然后,在使所有样本的类内近邻尽可能地聚集在一起的同时使...
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| 关 键 词： | 保局投影 鉴别分析 降维 模式分类 |
Sample locality preserving discriminant analysis for classification |
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| YANG Li-ping,GU Xiao-hua,YE Hong-wei. Sample locality preserving discriminant analysis for classification[J]. Optics and Precision Engineering, 2011, 19(9): 2205-2213. DOI: 10.3788/OPE.20111909.2205 |
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| Authors: | YANG Li-ping GU Xiao-hua YE Hong-wei |
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| Affiliation: | YANG Li-ping*,GU Xiao-hua,YE Hong-wei (Laboratory of Optoelectronic Technology and Systems of the Ministry of Education,Chongqing University,Chongqing 400044,China) |
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| Abstract: | The small sample size and the loss of effective dimension problems always exist in discriminative dimension reduction methods of high-dimensional data classification.To address these problems,a Sample Locality Preserving Discriminant Analysis(SLPDA) method is proposed by integrating the latest patch alignment framework and Locality Preserving Projections(LPP).The within-class and out-class neighborhood relationships of all samples in the SLPDA are constructed by summing the within-class and out-class neighb... |
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| Keywords: | locality preserving projection discriminant analysis dimension reduction pattern classification |
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