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A sparse regression method for group-wise feature selection with false discovery rate control
The method of Sorted L-One Penalized Estimation, or SLOPE, is a sparse regression method recently introduced by Bogdan et. al. [1]. It can be used to identify significant predictor variables in a linear model that may have more unknown parameters than observations. When the correlations between pred...
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| Veröffentlicht in: | IEEE/ACM Trans Comput Biol Bioinform |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2017
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6326365/ https://ncbi.nlm.nih.gov/pubmed/29990279 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TCBB.2017.2780106 |
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