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Local mean representation based classifier and its applications for data classification

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Abstract

Data classification is a fundamental problem in many research areas. This paper proposes a novel classifier, namely local mean representation based classifier (LMRC), for data classification. Based on the concept that neighboring samples should have most similar properties and for a testing sample, the similar properties should be concentrated on the mean of its intra-class nearest neighbors, LMRC represents the testing sample as a linear combination of its all local class means and assigns the testing sample to the class associating with the biggest item of the linear combination coefficient vector. LMRC is easy to employ with a least squares estimator, and it needs not to tune any parameter and could explore the local neighborhood relationship between samples to enhance the classification performance. Furthermore, to deal with the nonlinear problems, we extend the linear LMRC to its kernel version called kernel LMRC (KLMRC). Experiments on some benchmark datasets validate the superiority of the proposed two methods over other state-of-the-art methods.

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Acknowledgements

This work is sponsored by the National Natural Science Foundation of China (Grant Nos. 61503195 and 61502245), the China Postdoctoral Science Foundation (Grant Nos. 2015M571786 and 2016M600433), the Natural Science Foundation of Jiangsu Province (Grant Nos. BK20150849 and BK20161580), a Project funded by the PAPD and CICAEET, and Project supported by the Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology) (Grant No. 30916014107).

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Authors and Affiliations

  1. School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210023, Jiangsu, China

    Pu Huang & Geng Yang

  2. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Chengshan Qian

  3. Key Laboratory of Image and Video Understanding for Social Safety, Nanjing University of Science and Technology, Nanjing, 210094, China

    Pu Huang

  4. School of Computer, Nanjing University of Science and Technology, Nanjing, 210094, China

    Juliang Hua

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  1. Pu Huang
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Correspondence to Pu Huang.

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Huang, P., Qian, C., Yang, G. et al. Local mean representation based classifier and its applications for data classification. Int. J. Mach. Learn. & Cyber. 9, 969–978 (2018). https://doi.org/10.1007/s13042-016-0621-0

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  • DOI: https://doi.org/10.1007/s13042-016-0621-0

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