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Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms
BACKGROUND: Data generated using 'omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of subjects in the study. In this paper, we consider issues relevant in the design of biomedical studies in which the...
| Autores principales: | , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2010
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2942858/ https://www.ncbi.nlm.nih.gov/pubmed/20815881 http://dx.doi.org/10.1186/1471-2105-11-447 |