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Self-tuning clustering for high-dimensional data

  • Guoqiu Wen
  • Yonghua Zhu
  • Zhiguo Cai
  • Wei Zheng
Article
  • 27 Downloads
Part of the following topical collections:
  1. Special Issue on Deep Mining Big Social Data

Abstract

Spectral clustering is an important component of clustering method, via tightly relying on the affinity matrix. However, conventional spectral clustering methods 1). equally treat each data point, so that easily affected by the outliers; 2). are sensitive to the initialization; 3). need to specify the number of cluster. To conquer these problems, we have proposed a novel spectral clustering algorithm, via employing an affinity matrix learning to learn an intrinsic affinity matrix, using the local PCA to resolve the intersections; and further taking advantage of a robust clustering that is insensitive to initialization to automatically generate clusters without an input of number of cluster. Experimental results on both artificial and real high-dimensional datasets have exhibited our proposed method outperforms the clustering methods under comparison in term of four clustering metrics.

Keywords

Spectral clustering Local PCA Multi-manifold clustering High-dimensional data 

Notes

Acknowledgements

This work is partially supported by the China Key Research Program (Grant No: 2016YFB1000905); the Natural Science Foundation of China (Grants No: 61573270 and 6167217); the Project of Guangxi Science and Technology (GuiKeAD17195062); the Guangxi Natural Science Foundation (Grant No: 2015GXNSFCB139011); Innovation Project of Guangxi Graduate Education (Grant No: YCSW2018093); the Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing; the Guangxi High Institutions Program of Introducing 100 High-Level Overseas Talents; and the Research Fund of Guangxi Key Lab of Multisource Information Mining & Security (18-A-01-01).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Guoqiu Wen
    • 1
  • Yonghua Zhu
    • 2
  • Zhiguo Cai
    • 3
  • Wei Zheng
    • 1
  1. 1.College of Computer Science and Information TechnologyGuangxi Normal UniversityGuilinPeople’s Republic of China
  2. 2.School of Computer, Electronics and InformationGuangxi UniversityNanningPeople’s Republic of China
  3. 3.School of Journalism and Communication of Yangzhou UniversityYangzhouPeople’s Republic of China

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