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Orthogonal margin discriminant projection for dimensionality reduction

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Abstract

Dimensionality reduction aims to represent high-dimensional data with much smaller number of features, which plays as a preprocessing step to remove the insignificant and irrelevant features in many machine learning applications, resulting in lower computational cost and better performance of classifiers. In most cases, the data points can be well classified with margin samples which are defined as furthest intra-class samples and nearest inter-class samples. Motivated by this observation, this paper proposes a linear supervised dimensionality reduction method called orthogonal margin discriminant projection (OMDP). After OMDP projection, intra-class data points become more compact and inter-class data points become more separated. Extensive experiments have been conducted to evaluate the proposed OMDP algorithm using several benchmark face data sets. The experimental results confirm the effectiveness of the proposed method.

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Notes

  1. http://www.sheffield.ac.uk/eee/research/iel/research/face.

  2. http://www.cad.zju.edu.cn/home/dengcai/Data/FaceData.html.

  3. http://www.uk.research.att.com/facedatabase.html.

  4. http://www.cad.zju.edu.cn/home/dengcai/Data/FaceData.html.

  5. http://cvc.yale.edu/projects/yalefaces/yalefaces.html.

  6. http://rvl1.ecn.purdue.edu/~aleix/aleix_face_DB.html.

  7. http://www.cs.nthu.edu.tw/~htchen/.

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Acknowledgments

The authors are very grateful to the anonymous referees for their valuable comments. This work was supported by Science Computing and Intelligent Information Processing of Guangxi Hhigher Education Key Laboratory (No. GXSCIIP201406).

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Authors and Affiliations

  1. College of Information Engineering, Northwest A & F University, Yangling, 712100, Shaanxi Province, China

    Jinrong He

  2. School of Computer, Wuhan University, Wuhan, 430072, China

    Di Wu

  3. Department of Computer Science, Georgia State University, Atlanta, GA, 30303, USA

    Naixue Xiong

  4. School of Science, Wuhan University of Technology, Wuhan, 430070, China

    Chuansheng Wu

  5. Science Computing and Intelligent Information Processing of Guangxi Higher Education Key Laboratory, Guangxi Teachers Education University, Nanning, 530023, China

    Jinrong He

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  1. Jinrong He
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Correspondence to Jinrong He.

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He, J., Wu, D., Xiong, N. et al. Orthogonal margin discriminant projection for dimensionality reduction. J Supercomput 72, 2095–2110 (2016). https://doi.org/10.1007/s11227-015-1453-5

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  • DOI: https://doi.org/10.1007/s11227-015-1453-5

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