Locality Sensitive Proximal Classifier with Consistency for Small Sample Size Problem

Abstract

The proximal classifier with consistency (PCC) is an improvement of generalized eigenvalue proximal support vector machine (GEPSVM), ensuring consistency ignored in GEPSVM. However, similar to many other machine learning methods, PCC uses only the global information and the eigenvalue problem need to be solved, which can not classify small sample size (SSS… (More)
DOI: 10.1109/ICDMW.2015.180

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Cite this paper

@article{Shao2015LocalitySP, title={Locality Sensitive Proximal Classifier with Consistency for Small Sample Size Problem}, author={Yuan-Hai Shao and Zhen Wang and Chun-Na Li and Nai-Yang Deng}, journal={2015 IEEE International Conference on Data Mining Workshop (ICDMW)}, year={2015}, pages={1163-1170} }