Stochastic convex sparse principal component analysis

Principal component analysis (PCA) is a dimensionality reduction and data analysis tool commonly used in many areas. The main idea of PCA is to represent high-dimensional data with a few representative components that capture most of the variance present in the data. However, there is an obvious dis...

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Detalles Bibliográficos
Autores principales: Baytas, Inci M., Lin, Kaixiang, Wang, Fei, Jain, Anil K., Zhou, Jiayu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5018037/
https://www.ncbi.nlm.nih.gov/pubmed/27660635
http://dx.doi.org/10.1186/s13637-016-0045-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5018037/
https://www.ncbi.nlm.nih.gov/pubmed/27660635
http://dx.doi.org/10.1186/s13637-016-0045-x

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