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of 133
pro vyhledávání: '"Lynn, Henry S"'
Missing data are common in data analyses in biomedical fields, and imputation methods based on random forests (RF) have become widely accepted, as the RF algorithm can achieve high accuracy without the need for specification of data distributions or
Externí odkaz:
http://arxiv.org/abs/2004.14823
Machine learning iterative imputation methods have been well accepted by researchers for imputing missing data, but they can be time-consuming when handling large datasets. To overcome this drawback, parallel computing strategies have been proposed b
Externí odkaz:
http://arxiv.org/abs/2004.11195
Publikováno v:
In Journal of the National Cancer Center December 2023 3(4):279-285
Autor:
Yin, Ruoyu, Wang, Yinsu, Li, Yaxi, Lynn, Henry S., Zhang, Yueqian, Jin, Xurui, Yan, Lijing L.
Publikováno v:
In Preventive Medicine October 2023 175
Publikováno v:
In eClinicalMedicine March 2022 45
Autor:
Hong, Shangzhi, Liu, Fengfeng, Bauer, Cici, Chen, Yue, Tu, Wei, Zhang, Jun, Hu, Jian, Zhang, Wenyi, Hu, Yi, Lynn, Henry S., Li, Yu, Chang, Zhaorui, Li, Zhongjie, Zhang, Zhijie
Publikováno v:
In Science of the Total Environment 25 June 2021 775
Autor:
Lynn, Henry S.
Publikováno v:
The American Statistician, 2003 Feb 01. 57(1), 58-61.
Externí odkaz:
https://www.jstor.org/stable/3087279
Autor:
Lynn, Henry S., McCulloch, Charles E.
Publikováno v:
Journal of the American Statistical Association, 2000 Jun 01. 95(450), 561-572.
Externí odkaz:
https://www.jstor.org/stable/2669399
Akademický článek
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Autor:
Lynn, Henry S.
Publikováno v:
The American Statistician, 2016 May 01. 70(2), 149-151.
Externí odkaz:
https://www.jstor.org/stable/45118300