SSRNML & AI Methods
Validity of Post hoc Explanations
The research explores the effectiveness of post hoc explainers, SHAP and LIME, in determining the significance of variables in machine learning models, questioning their accuracy in revealing the real marginal effects of these variables.
Featured in No. 60 on 7 Aug 2024 · 4 days after release
- Released
- 3 Aug 2024
- First featured
- No. 60 · 7 Aug 2024
- Published in
- Not yet, as far as Semantic Scholar knows
- Shares when featured
- 2
- Identifier
- SSRN 4915307
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