Local Explanations
Local Explanations is a type of interpretability method in machine learning that provides insight into a model's behavior by approximating its decision process in the vicinity of a specific input instance, thereby distinguishing itself from global explanations that aim to characterize overall model behavior.
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34.6K
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1K
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470
Institutions
Publications per year
2017–2026
278
309
From local explanations to global understanding with explainable AI for trees
Scott Lundberg, Gabriel Erion, Hugh Chen et al. · Nature Machine Intelligence · 2020 · 8.9K citations · Full text
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University of Washington
Seattle, United States
9 h-index
28 publications
111.5K citations

University of Pisa
Pisa, Italy
6 h-index
25 publications
3.6K citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
20 publications
871 citations
University of California, Irvine
Irvine, United States
5 h-index
6 publications
2.6K citations
University of Florida
Gainesville, United States
4 h-index
8 publications
354 citations
Google (United States)
Mountain View, United States
4 h-index
9 publications
404 citations
Columbia University
New York, United States
4 h-index
4 publications
247 citations
University of Cambridge
Cambridge, United Kingdom
4 h-index
10 publications
409 citations
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Repository · 64 publications · 2.8K citations
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11 publications · 861 citations
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Repository · 7 publications · 242 citations
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Conference · 7 publications · 2.4K citations
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6 publications · 326 citations
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