Adaptive Graph Regularized Low–Rank Matrix Factorization With Noise and Outliers for Clustering
Clustering, which is a commonly used tool, has been applied in machine learning, data mining and so on, and has received extensive research. However, there are usually noise and outliers in the data, which will bring about significant errors in the clustering results. In this paper, a robust cluster...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9201009/ |