A New Method Combining LDA and PLS for Dimension Reduction. | |
Tang, Liang; Peng, Silong; Bi, Yiming; Shan, Peng; Hu, Xiyuan, | |
发表期刊 | PLos One |
2014 | |
卷号 | 9(5)期号:5页码:e96944-e96944 (SCI) |
摘要 | Linear discriminant analysis (LDA) is a classical statistical approach for dimensionality reduction and classification. In many cases, the projection direction of the classical and extended LDA methods is not considered optimal for special applications. Herein we combine the Partial Least Squares (PLS) method with LDA algorithm, and then propose two improved methods, named LDA-PLS and ex-LDA-PLS, respectively. The LDA-PLS amends the projection direction of LDA by using the information of PLS, while ex-LDA-PLS is an extension of LDA-PLS by combining the result of LDA-PLS and LDA, making the result closer to the optimal direction by an adjusting parameter. Comparative studies are provided between the proposed methods and other traditional dimension reduction methods such as Principal component analysis (PCA), LDA and PLS-LDA on two data sets. Experimental results show that the proposed method can achieve better classification performance. |
关键词 | Modified Split Hopkinson Torsional Bars Shear Localization Microstructural Evolution |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/12907 |
专题 | 智能制造技术与系统研究中心_多维数据分析 |
通讯作者 | Tang, Liang |
推荐引用方式 GB/T 7714 | Tang, Liang,Peng, Silong,Bi, Yiming,et al. A New Method Combining LDA and PLS for Dimension Reduction.[J]. PLos One,2014,9(5)(5):e96944-e96944 (SCI). |
APA | Tang, Liang,Peng, Silong,Bi, Yiming,Shan, Peng,&Hu, Xiyuan,.(2014).A New Method Combining LDA and PLS for Dimension Reduction..PLos One,9(5)(5),e96944-e96944 (SCI). |
MLA | Tang, Liang,et al."A New Method Combining LDA and PLS for Dimension Reduction.".PLos One 9(5).5(2014):e96944-e96944 (SCI). |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
A New Method Combini(770KB) | 期刊论文 | 作者接受稿 | 暂不开放 | CC BY-NC-SA |
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