The details can be found in the IEEE TSMCA.
Some Incomplete multi-view clustering (IMC) used in the paper are collected from the following websites:
For PMVC: The code of PMVC is released by the authors and can be download from the authors homepage: http://parnec.nuaa.edu.cn/lisy/
S.-Y. Li, Y. Jiang, and Z.-H. Zhou, Partial multi-view clustering, in AAAI Conference on Artificial Intelligence, pp. 1969--1974, 2014.
For MIC and OMVC: Codes can be download from the authors' homepage at https://www.cs.uic.edu/~wshao/
For kenerl learning based IMC, the source code can be downloaded from: https://github.com/wangsiwei2010/multiple_kernel_clustering_with_absent_kernel
For incomplete multi-view data construction, you can use code 'splitDigitData.m' to generate the index of missing views.
You may download the datasets from baiduyun Code: t98h; After that, you can add these datasets to the 'dataset' fold.
If you use the matlab code here, please cite our paper below:
J. Wen, Z. Zhang, L. Fei, B. Zhang, Y. Xu, Z. Zhang, J. Li, A Survey on Incomplete Multi-view Clustering, IEEE Transactions on Systems, Man and Cybernetics: Systems (TSMCA), 2022.
If you have any question, please contact us: jiewen_pr@126.com, or darrenzz219@gmail.com
@article{wen2022survey,
title={A Survey on Incomplete Multi-view Clustering},
author={Wen, Jie and Zhang, Zheng and Fei, Lunke and Zhang, Bob and Xu, Yong and Zhang, Zhao and Li, Jinxing},
journal={IEEE Transactions on Systems, Man and Cybernetics: Systems},
volume={x},
pages={xxxx--xxxx},
year={2022},
publisher={IEEE}
}