Feature Interaction Attribution
Feature Interaction Attribution is an academic method that identifies and quantifies the contribution of interactions among input features to the output of a predictive model, distinguishing it from feature attribution methods that assess individual feature importance in isolation.
6
Publications
252
Citations
15
Authors
9
Institutions
Publications per year
2017–2026
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Stanford University
Stanford, United States
2 h-index
8 publications
412 citations
Chan Zuckerberg Initiative (United States)
Redwood City, United States
2 h-index
2 publications
103 citations
University of Virginia
Charlottesville, United States
1 h-index
3 publications
90 citations
University of Washington
Seattle, United States
1 h-index
3 publications
129 citations
California Southern University
Chandler, United States
1 h-index
3 publications
102 citations
University of Southern California
Los Angeles, United States
1 h-index
3 publications
102 citations
Cardiovascular Institute of the South
Houma, United States
1 h-index
1 publications
11 citations
RWTH Aachen University
Aachen, Germany
1 h-index
3 publications
90 citations
1–8 of 9
Repository · 2 publications · 77 citations
2
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Repository · 1 publications · 11 citations
1
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1 publications · 92 citations
1
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1 publications · 42 citations
1
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Conference · 1 publications · 12 citations
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