What is recorded here?
Defined the SHAP framework for local feature attribution, identified a class of additive feature-attribution methods and gave uniqueness results under the paper’s stated properties.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The record is the exact NIPS 2017 two-author paper. Shapley’s game-theoretic value, LIME, DeepLIFT, later TreeSHAP implementations and claims about causal explanation or universal faithfulness remain separate.
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People and systems
Scott M. Lundberg; Su-In Lee
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.
Research locations and affiliations
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Documented countries / regions: United States
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English catalogue narrative
Lundberg and Lee: a unified approach to interpreting model predictions
Defined the SHAP framework for local feature attribution, identified a class of additive feature-attribution methods and gave uniqueness results under the paper’s stated properties.
Scientific scope
The record is the exact NIPS 2017 two-author paper. Shapley’s game-theoretic value, LIME, DeepLIFT, later TreeSHAP implementations and claims about causal explanation or universal faithfulness remain separate.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Scott M. Lundberg; Su-In Lee
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.