Big Data Regression is a machine learning methodology that extends classical regression techniques to model relationships in large-scale, high-dimensional, and distributed datasets by incorporating scalable algorithms and computational frameworks to address volume, velocity, and variety challenges inherent in big data environments.
63
Publications
4.8K
Citations
164
Authors
105
Institutions
Publications per year
2017–2026
49
Publications
63
CatBoost for big data: an interdisciplinary review
John Hancock, Taghi M. Khoshgoftaar · Journal Of Big Data · 2020 · 1.7K citations · Full text
Medical big data: promise and challenges
Choong Ho Lee, Hyung‐Jin Yoon · Kidney Research and Clinical Practice · 2017 · 597 citations · Full text
1–5 of 63
Authors
164
- JH
3
h-index
- TM
3
h-index
- TF
2
h-index
- TZ
2
h-index
- AC
2
h-index
1–5 of 164
Institutions
105
City University of Hong Kong
Hong Kong, Hong Kong
3 h-index
3 publications
147 citations
University of Illinois Chicago
Chicago, United States
3 h-index
3 publications
433 citations
Florida Atlantic University
Boca Raton, United States
3 h-index
6 publications
3.4K citations
University of Connecticut
Storrs, United States
3 h-index
3 publications
433 citations
Central University of Finance and Economics
Beijing, China
2 h-index
3 publications
96 citations
University of Pennsylvania
Philadelphia, United States
2 h-index
5 publications
389 citations
Purdue University West Lafayette
West Lafayette, United States
2 h-index
4 publications
120 citations
University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
5 publications
95 citations
1–8 of 105
Venues
- Research Square
Repository · 2 publications · 48 citations
2
h-index
- International Statistical Review
2 publications · 86 citations
2
h-index
- Technometrics
2 publications · 55 citations
2
h-index
- Journal of Applied Statistics
2 publications · 45 citations
2
h-index
- Data & Knowledge Engineering
DKE · 2 publications · 44 citations
2
h-index
1–5