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Journal of Applied Statistics Volume 50, 2023 - Issue 3: Statistical Approaches for Big Data and Machine Learning
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Handling high-dimensional data with missing values by modern machine learning techniques

Sixia ChenDepartment of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-7502-2587View further author information
ORCID Icon &
Chao XuDepartment of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USAORCID Iconhttps://orcid.org/0000-0002-3821-6187View further author information
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Pages 786-804 | Received 28 Sep 2020, Accepted 16 Apr 2022, Published online: 01 May 2022

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Yichuan Zhao, Chi-Hua Chen, Feng Feng & Dragan Pamucar. (2023) Editorial to the special issue: Statistical Approaches for Big Data and Machine Learning. Journal of Applied Statistics 50:3, pages 451-455.
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Articles from other publishers (2)

Mingxuan Liu, Siqi Li, Han Yuan, Marcus Eng Hock Ong, Yilin Ning, Feng Xie, Seyed Ehsan Saffari, Yuqing Shang, Victor Volovici, Bibhas Chakraborty & Nan Liu. (2023) Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. Artificial Intelligence in Medicine 142, pages 102587.
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Maoni Jia, Yafei Wu, Chaoyi Xiang & Ya Fang. (2023) Predicting Alzheimer’s Disease with Interpretable Machine Learning. Dementia and Geriatric Cognitive Disorders 52:4, pages 249-257.
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