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...

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Detalles Bibliográficos
Autores principales: Guo, Yu, Graber, Armin, McBurney, Robert N, Balasubramanian, Raji
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Research Article
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

Internet

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

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