Machine Learning Feature Engineering
Machine Learning Feature Engineering is a methodological process in which domain-specific transformations are applied to raw data to construct informative and non-redundant features that enhance the performance of machine learning models in predicting phenotypic outcomes.
305
Publications
16.1K
Citations
1.5K
Authors
703
Institutions
Publications per year
2017–2026
259
305
1–5 of 305
1.5K
3
h-index
University of Electronic Science and Technology of China, China
3 publications · 199 citations
3
h-index
Khwaja Fareed University of Engineering and Information Technology, Pakistan
3 publications · 289 citations
3
h-index
Noakhali Science and Technology University, Bangladesh
3 publications · 290 citations
3
h-index
Khwaja Fareed University of Engineering and Information Technology, Pakistan
3 publications · 289 citations
3
h-index
1–5 of 1.5K
703

University of Electronic Science and Technology of China
Chengdu, China
5 h-index
9 publications
605 citations
Vellore Institute of Technology University
Vellore, India
4 h-index
9 publications
628 citations
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
11 publications
708 citations

University of Toronto
Toronto, Canada
4 h-index
7 publications
622 citations
Texas A&M University
College Station, United States
4 h-index
11 publications
1.8K citations

Zhejiang University
Hangzhou, China
4 h-index
20 publications
1.1K citations
Chandigarh University
Mohali, India
3 h-index
11 publications
262 citations
Prince Sattam Bin Abdulaziz University
Al Kharj, Saudi Arabia
3 h-index
3 publications
89 citations
1–8 of 703
12 publications · 481 citations
12
h-index
11 publications · 347 citations
11
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10 publications · 815 citations
10
h-index
7 publications · 448 citations
7
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6 publications · 112 citations
6
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1–5