Clustering Ensemble Based on Sample’s Certainty

Author:

Ji Xia,Liu Shuaishuai,Zhao Peng,Li Xuejun,Liu Qiong

Funder

Natural Science Foundation of China

Key Research and Development Program of Anhui Province

Natural Science Foundation of Anhui Province

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Reference45 articles.

1. Verma M, Srivastava M, Chack N, Diswar AK, Gupta N. A comparative study of various clustering algorithms in data mining. Int J Eng Res Appl (IJERA). 2012;2(3):1379–84.

2. Abualigah LM, Khader AT, Al-Betar MA. Unsupervised feature selection technique based on genetic algorithm for improving the text clustering; In: Proceedings of the 2016 7th international conference on computer science and information technology (CSIT), 2016. IEEE.

3. Elankavi R, Kalaiprasath R, Udayakumar DR. A fast clustering algorithm for high-dimensional data. International Journal of Civil Engineering and Technology (IJCIET). 2017;8(5):1220–7.

4. Kang Z, Pan H, Hoi SC, Xu Z. Robust graph learning from noisy data. IEEE transactions on cybernetics. 2019;50(5):1833–43.

5. Strehl A, Ghosh J. Cluster ensembles-a knowledge reuse framework for combining multiple partitions. J Mach Learn Res. 2002, 3(Dec);583–617.

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