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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...
Autores principales: | Santana, Adrielle C., Barbosa, Adriano V., Yehia, Hani C., Laboissière, Rafael |
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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/PMC7780417/ https://www.ncbi.nlm.nih.gov/pubmed/33397293 http://dx.doi.org/10.1186/s12868-020-00605-0 |
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