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A multiple hold-out framework for Sparse Partial Least Squares
BACKGROUND: Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (SPLS), may provide insights into the brain's...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier/North-Holland Biomedical Press
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012894/ https://www.ncbi.nlm.nih.gov/pubmed/27353722 http://dx.doi.org/10.1016/j.jneumeth.2016.06.011 |