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Harvestman: a framework for hierarchical feature learning and selection from whole genome sequencing data
BACKGROUND: Supervised learning from high-throughput sequencing data presents many challenges. For one, the curse of dimensionality often leads to overfitting as well as issues with scalability. This can bring about inaccurate models or those that require extensive compute time and resources. Additi...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017869/ https://www.ncbi.nlm.nih.gov/pubmed/33794760 http://dx.doi.org/10.1186/s12859-021-04096-6 |