Cargando…
Variable Selection in the Regularized Simultaneous Component Analysis Method for Multi-Source Data Integration
Interdisciplinary research often involves analyzing data obtained from different data sources with respect to the same subjects, objects, or experimental units. For example, global positioning systems (GPS) data have been coupled with travel diary data, resulting in a better understanding of traveli...
Autores principales: | Gu, Zhengguo, Schipper, Niek C. de, Van Deun, Katrijn |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901488/ https://www.ncbi.nlm.nih.gov/pubmed/31819077 http://dx.doi.org/10.1038/s41598-019-54673-2 |
Ejemplares similares
-
RegularizedSCA: Regularized simultaneous component analysis of multiblock data in R
por: Gu, Zhengguo, et al.
Publicado: (2018) -
Simultaneous clustering and variable selection: A novel algorithm and model selection procedure
por: Yuan, Shuai, et al.
Publicado: (2022) -
Revealing the Joint Mechanisms in Traditional Data Linked With Big
Data
por: de Schipper, Niek C., et al.
Publicado: (2019) -
A structured overview of simultaneous component based data integration
por: Van Deun, Katrijn, et al.
Publicado: (2009) -
A flexible framework for sparse simultaneous component based data integration
por: Van Deun, Katrijn, et al.
Publicado: (2011)