AI Governance Engineer
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LIME

By Updated

Local Interpretable Model-agnostic Explanations: explains one prediction by fitting a simple interpretable model to the black box's behaviour on perturbed samples around the input 1; vulnerable to off-manifold manipulation.

Developed in
ch. 16, Feature attribution: SHAP, LIME and integrated gradients
Chapters
ch. 16, Fairness & XAI
Contrast with
SHAP
Source
1 numbered reference, listed below

Where it is used

One chapter of the Body of Knowledge uses the term. Each link opens the first section that does.

Patterns that use this term

One pattern page uses the term.

Sources

  1. [1] "'Why Should I Trust You?': Explaining the Predictions of Any Classifier" (Ribeiro, Singh and Guestrin; LIME; arXiv 1602.04938). arXiv. 2016-02-16. https://arxiv.org/abs/1602.04938 (verified: primary)

Definitions of legal terms paraphrase the cited text, which governs. Dated statements are as of .

Cite this term

García Aibar, J. (2026). LIME. In AI Governance Engineering: The Thesis & Body of Knowledge (v0.5.0), Glossary. https://doi.org/10.5281/zenodo.22956197. https://aigovernanceengineer.com/glossary/lime. CC BY 4.0

BibTeX

@misc{aige2026lime,
  author  = {Jorge García Aibar},
  title   = {{LIME}},
  note    = {Glossary, AI Governance Engineering: The Thesis \& Body of Knowledge, version 0.5.0},
  year    = {2026},
  doi     = {10.5281/zenodo.22956197},
  url     = {https://aigovernanceengineer.com/glossary/lime}
}