Supervised dimensionality reduction for big data

Biomedical measurements usually generate high-dimensional data where individual samples are classified in several categories. Vogelstein et al. propose a supervised dimensionality reduction method which estimates the low-dimensional data projection for classification and prediction in big datasets.

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Detalles Bibliográficos
Autores principales:	Joshua T. Vogelstein, Eric W. Bridgeford, Minh Tang, Da Zheng, Christopher Douville, Randal Burns, Mauro Maggioni
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/4e96486444d04876a7a760151e1835c7
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id	oai:doaj.org-article:4e96486444d04876a7a760151e1835c7
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spelling	oai:doaj.org-article:4e96486444d04876a7a760151e1835c72021-12-02T16:51:25ZSupervised dimensionality reduction for big data10.1038/s41467-021-23102-22041-1723https://doaj.org/article/4e96486444d04876a7a760151e1835c72021-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23102-2https://doaj.org/toc/2041-1723Biomedical measurements usually generate high-dimensional data where individual samples are classified in several categories. Vogelstein et al. propose a supervised dimensionality reduction method which estimates the low-dimensional data projection for classification and prediction in big datasets.Joshua T. VogelsteinEric W. BridgefordMinh TangDa ZhengChristopher DouvilleRandal BurnsMauro MaggioniNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Joshua T. Vogelstein Eric W. Bridgeford Minh Tang Da Zheng Christopher Douville Randal Burns Mauro Maggioni Supervised dimensionality reduction for big data
description	Biomedical measurements usually generate high-dimensional data where individual samples are classified in several categories. Vogelstein et al. propose a supervised dimensionality reduction method which estimates the low-dimensional data projection for classification and prediction in big datasets.
format	article
author	Joshua T. Vogelstein Eric W. Bridgeford Minh Tang Da Zheng Christopher Douville Randal Burns Mauro Maggioni
author_facet	Joshua T. Vogelstein Eric W. Bridgeford Minh Tang Da Zheng Christopher Douville Randal Burns Mauro Maggioni
author_sort	Joshua T. Vogelstein
title	Supervised dimensionality reduction for big data
title_short	Supervised dimensionality reduction for big data
title_full	Supervised dimensionality reduction for big data
title_fullStr	Supervised dimensionality reduction for big data
title_full_unstemmed	Supervised dimensionality reduction for big data
title_sort	supervised dimensionality reduction for big data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/4e96486444d04876a7a760151e1835c7
work_keys_str_mv	AT joshuatvogelstein superviseddimensionalityreductionforbigdata AT ericwbridgeford superviseddimensionalityreductionforbigdata AT minhtang superviseddimensionalityreductionforbigdata AT dazheng superviseddimensionalityreductionforbigdata AT christopherdouville superviseddimensionalityreductionforbigdata AT randalburns superviseddimensionalityreductionforbigdata AT mauromaggioni superviseddimensionalityreductionforbigdata
_version_	1718382975923519488

Supervised dimensionality reduction for big data

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