Construct · 1 fields · 1 citations

SHapley Additive exPlanations: a standalone construct

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Deep learning

a feature attribution framework that assigns each input feature its Shapley value contribution to a single model prediction, unifying several earlier explanation methods.

In deep learning, SHapley Additive exPlanations refers to a feature attribution framework that assigns each input feature its Shapley value contribution to a single model prediction, unifying several earlier explanation methods. This meaning comes from Lundberg (2017) in arXiv.[1]

Unit
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Nearby constructs

attribution3 fields · 6 citationsjingle · one word, three constructs contribution2 fields · 3 citationsjingle · one word, two carriers deep learning1 fields · 1 citationsanchor · a standalone construct

References

Lundberg, S., & Lee, S. (2017). A Unified Approach to Interpreting Model Predictions. arXiv. https://doi.org/10.48550/arxiv.1705.07874

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