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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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Podrobná bibliografie
Vydáno v:EURASIP J Bioinform Syst Biol
Hlavní autoři: Baytas, Inci M., Lin, Kaixiang, Wang, Fei, Jain, Anil K., Zhou, Jiayu
Médium: Artigo
Jazyk:Inglês
Vydáno: Springer International Publishing 2016
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC5018037/
https://ncbi.nlm.nih.gov/pubmed/27660635
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13637-016-0045-x
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