Consensus Feature Selection
Consensus Feature Selection is a feature selection strategy that identifies a stable subset of predictive variables by aggregating multiple feature rankings derived from heterogeneous data samples, models, or algorithms to enhance robustness and generalizability.
31
Publications
1.7K
Citations
133
Authors
75
Institutions
Publications per year
2017–2026
19
Variants
Stable Feature Selection
Parents
31
Consensus features nested cross-validation
Saeid Parvandeh, Hung‐Wen Yeh, Martin P. Paulus et al. · Bioinformatics · 2020 · 219 citations · Full text
Consensus group stable feature selection
Steven Loscalzo, Lei Yu, Chris Ding · 2009 · 141 citations
Computing, Data Science, Data Mining +12
Consensus unsupervised feature ranking from multiple views
Yi Hong, Sam Kwong, Yuchou Chang et al. · Pattern Recognition Letters · 2007 · 80 citations
1–5 of 31
133
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h-index
3
h-index
2
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2
h-index
First Affiliated Hospital of Guangzhou Medical University, China
1 publications · 63 citations
1
h-index
1–5 of 133
75
Ningbo University
Ningbo, China
3 h-index
8 publications
467 citations

China Mobile (China)
Beijing, China
2 h-index
5 publications
266 citations
University of Technology Sydney
Sydney, Australia
2 h-index
3 publications
189 citations

City University of Hong Kong
Hong Kong, Hong Kong
2 h-index
5 publications
259 citations
State Key Laboratory of Respiratory Disease
Guangzhou, China
1 h-index
12 publications
756 citations
Binghamton University
Binghamton, United States
1 h-index
2 publications
282 citations
Northeastern University
Boston, United States
1 h-index
1 publications
33 citations
Universidad del Noreste
Tampico, Mexico
1 h-index
3 publications
108 citations
1–8 of 75
3 publications · 133 citations
3
h-index
2 publications · 93 citations
2
h-index
2 publications · 81 citations
2
h-index
TKDE · 2 publications · 73 citations
2
h-index
2 publications · 85 citations
2
h-index
1–5