A truncated nuclear norm and graph-Laplacian regularized low-rank representation method for tumor clustering and gene selection
Abstract Background Clustering and feature selection act major roles in many communities. As a matrix factorization, Low-Rank Representation (LRR) has attracted lots of attentions in clustering and feature selection, but sometimes its performance is frustrated when the data samples are insufficient...
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| Format: | Article |
| Language: | English |
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BMC
2022-01-01
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| Series: | BMC Bioinformatics |
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| Online Access: | https://doi.org/10.1186/s12859-021-04333-y |