Categorical Data Representation is a data representation method that encodes categorical variables by mapping discrete categories to symbolic or numerical forms while preserving their qualitative distinctions and enabling computational processing.
1.1K
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103.4K
Citations
2.8K
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1.2K
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Publications per year
2017–2026
285
Parents
Publications
1.1K
1–5 of 1.1K
Authors
2.8K
- JL
13
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- LC
11
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- FC
10
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- MF
9
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- ZH
9
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1.2K
Shanxi University
Taiyuan, China
15 h-index
53 publications
2.2K citations
Hong Kong Baptist University
Hong Kong, Hong Kong
12 h-index
23 publications
1.6K citations
University of Minnesota
Minneapolis, United States
12 h-index
25 publications
2.4K citations
University of Technology Sydney
Sydney, Australia
12 h-index
29 publications
1.1K citations
Stanford University
Stanford, United States
12 h-index
17 publications
977 citations
University of Michigan
Ann Arbor, United States
11 h-index
17 publications
1.9K citations
Carnegie Mellon University
Pittsburgh, United States
10 h-index
14 publications
1.4K citations
National University of Defense Technology
Changsha, China
9 h-index
23 publications
714 citations
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- Journal of the American Statistical Association
33 publications · 5.5K citations
25
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- Technometrics
19 publications · 7.3K citations
17
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- Statistics in Medicine
18 publications · 848 citations
16
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- Biometrics
18 publications · 2.8K citations
16
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- arXiv (Cornell University)
Repository · 18 publications · 762 citations
13
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