A dimension reduction technique applied to regression on high dimension, low sample size neurophysiological data sets

BACKGROUND: A common problem in neurophysiological signal processing is the extraction of meaningful information from high dimension, low sample size data (HDLSS). We present RoLDSIS (regression on low-dimension spanned input space), a regression technique based on dimensionality reduction that cons...

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Detalles Bibliográficos
Autores principales: Santana, Adrielle C., Barbosa, Adriano V., Yehia, Hani C., Laboissière, Rafael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780417/
https://www.ncbi.nlm.nih.gov/pubmed/33397293
http://dx.doi.org/10.1186/s12868-020-00605-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780417/
https://www.ncbi.nlm.nih.gov/pubmed/33397293
http://dx.doi.org/10.1186/s12868-020-00605-0

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