Cargando…
Big data ordination towards intensive care event count cases using fast computing GLLVMS
BACKGROUND: In heart data mining and machine learning, dimension reduction is needed to remove multicollinearity. Meanwhile, it has been proven to improve the interpretation of the parameter model. In addition, dimension reduction can also increase the time of computing in high dimensional data. MET...
Autores principales: | Caraka, Rezzy Eko, Chen, Rung-Ching, Huang, Su-Wen, Chiou, Shyue-Yow, Gio, Prana Ugiana, Pardamean, Bens |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8939086/ https://www.ncbi.nlm.nih.gov/pubmed/35313816 http://dx.doi.org/10.1186/s12874-022-01538-4 |
Ejemplares similares
-
Correction to: Big data ordination towards intensive care event count cases using fast computing GLLVMS
por: Caraka, Rezzy Eko, et al.
Publicado: (2022) -
Using Harris hawk optimization towards support vector regression to ozone prediction
por: Kurniawan, Robert, et al.
Publicado: (2022) -
Counting people inside a region-of-interest in CCTV footage with deep learning
por: Pardamean, Bens, et al.
Publicado: (2022) -
Free trade as domestic, economic, and strategic issues: a big data analytics approach
por: Karim, Moch Faisal, et al.
Publicado: (2023) -
Use of numerical and spatial information in ordinal counting by zebrafish
por: Potrich, Davide, et al.
Publicado: (2019)