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Mutual kNN based spectral clustering

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Abstract

The key step of spectral clustering is learning the affinity matrix to measure the similarity among data points. This paper proposes a new spectral clustering method, which uses mutual k nearest neighbor to obtain the affinity matrix by removing the influence of noise. Then, the characteristics of high-dimensional data are self-represented to ensure local important information of data by using affinity matrix in standardized processing. Furthermore, we also use the normalization method to further improve the performance of clustering. Experimental analysis on eight benchmark data sets showed that our proposed method outperformed the state-of-the-art clustering methods in terms of clustering performance such as cluster accuracy and normalized mutual information.

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Notes

  1. http://archive.ics.uci.edu/ml/.

  2. http://featureselection.asu.edu/datasets.php.

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Acknowledgments

This work is partially supported by the China Key Research Program (Grant No. 2016YFB1000905); the Key Program of the National Natural Science Foundation of China (Grant No. 61836016); the Natural Science Foundation of China (Grants Nos. 61876046, 61573270, 81701780 and 61672177); the Project of Guangxi Science and Technology (GuiKeAD17195062); the Guangxi Natural Science Foundation (Grant Nos. 2015GXNSFCB139011, 2017GXNSFBA198221); 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 and Security (18-A-01-01).

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Authors and Affiliations

  1. Guangxi Key Lab of Multi-source Information Mining and Security (MIMS), Guangxi Normal University, Guilin, 541004, People’s Republic of China

    Malong Tan, Shichao Zhang & Lin Wu

  2. School of Information Science and Engineering, Central South University, Changsha, 410083, Hunan, People’s Republic of China

    Shichao Zhang

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  1. Malong Tan
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Correspondence to Shichao Zhang.

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Tan, M., Zhang, S. & Wu, L. Mutual kNN based spectral clustering. Neural Comput & Applic 32, 6435–6442 (2020). https://doi.org/10.1007/s00521-018-3836-z

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