Mutual Information-based Selection
Mutual Information-Based Selection is a feature selection method that identifies relevant features by measuring the mutual information between each feature and the target variable, thereby distinguishing itself from other filter methods through its reliance on information-theoretic dependence as the criterion for selection.
136
Publications
13.9K
Citations
376
Authors
170
Institutions
Publications per year
2017–2026
40
Variants
Mutual Information Feature Selection
Parents
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376
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170
UCLouvain
Louvain-la-Neuve, Belgium
7 h-index
17 publications
1.6K citations

Shanghai Jiao Tong University
Shanghai, China
6 h-index
15 publications
1.5K citations

Harbin Institute of Technology
Harbin, China
4 h-index
9 publications
382 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
5 publications
434 citations

Queensland University of Technology
Brisbane, Australia
3 h-index
6 publications
280 citations
National University of Singapore
Singapore, Singapore
3 h-index
7 publications
447 citations
Jiangxi Agricultural University
Nanchang, China
3 h-index
5 publications
297 citations

City University of Hong Kong
Hong Kong, Hong Kong
3 h-index
8 publications
355 citations
1–8 of 170
13 publications · 893 citations
13
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9 publications · 1.1K citations
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7 publications · 933 citations
7
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4 publications · 380 citations
4
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4 publications · 307 citations
4
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1–5