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Controlled feature selection and compressive big data analytics: Applications to biomedical and health studies

The theoretical foundations of Big Data Science are not fully developed, yet. This study proposes a new scalable framework for Big Data representation, high-throughput analytics (variable selection and noise reduction), and model-free inference. Specifically, we explore the core principles of distri...

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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: Marino, Simeone, Xu, Jiachen, Zhao, Yi, Zhou, Nina, Zhou, Yiwang, Dinov, Ivo D.
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6116997/
https://ncbi.nlm.nih.gov/pubmed/30161148
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0202674
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