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Tensor-Decomposition-Based Unsupervised Feature Extraction Applied to Prostate Cancer Multiomics Data
The large p small n problem is a challenge without a de facto standard method available to it. In this study, we propose a tensor-decomposition (TD)-based unsupervised feature extraction (FE) formalism applied to multiomics datasets, in which the number of features is more than 100,000 whereas the n...
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| 出版年: | Genes (Basel) |
|---|---|
| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI
2020
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7763286/ https://ncbi.nlm.nih.gov/pubmed/33322492 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/genes11121493 |
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