Feature Screening
Feature Screening is a parametric performance analysis method that identifies and selects the most influential input variables by evaluating their individual contributions to output variability, thereby distinguishing itself from other analysis techniques through its focus on pre-modeling dimensionality reduction via univariate assessment.
153
Publications
10.2K
Citations
471
Authors
247
Institutions
Publications per year
2017–2026
100
153
Selection of relevant features and examples in machine learning
Avrim Blum, Pat Langley · Artificial Intelligence · 1997 · 3.3K citations
Ultrahigh dimensional feature selection: beyond the linear model.
Jianqing Fan, Richard J. Samworth, Yichao Wu · PubMed · 2009 · 402 citations · Full text
1–5 of 153
471
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Nanjing University of Information Science and Technology, China
3 publications · 55 citations
3
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1–5 of 471
247

Pennsylvania State University
State College, United States
11 h-index
21 publications
4.2K citations

Nanjing University of Information Science and Technology
Nanjing, China
7 h-index
17 publications
457 citations
Xiamen University
Xiamen, China
7 h-index
10 publications
2K citations

Central South University
Changsha, China
6 h-index
22 publications
602 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
6 publications
3.4K citations

Shanghai Jiao Tong University
Shanghai, China
4 h-index
15 publications
252 citations

Renmin University of China
Beijing, China
4 h-index
7 publications
176 citations

University of Georgia
Athens, United States
4 h-index
11 publications
246 citations
1–8 of 247
12 publications · 1.9K citations
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Repository · 6 publications · 181 citations
6
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CSDA · 5 publications · 97 citations
5
h-index
5 publications · 179 citations
5
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4 publications · 183 citations
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