Evaluating MASHAP as a faster alternative to LIME for model-agnostic machine learning interpretability
Summary
Evaluating MASHAP as a faster alternative to LIME for model-agnostic machine learning interpretability is a scholarly article[1].
Key Facts
Evaluating MASHAP as a faster alternative to LIME for model-agnostic machine learning interpretability's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Evaluating MASHAP as a faster alternative to LIME for model-agnostic machine learning interpretability. Retrieved May 24, 2026, from https://4ort.xyz/entity/evaluating-mashap-as-a-faster-alternative-to-lime-for-model-agnostic-machine-learning-interpretability
MLA“Evaluating MASHAP as a faster alternative to LIME for model-agnostic machine learning interpretability.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/evaluating-mashap-as-a-faster-alternative-to-lime-for-model-agnostic-machine-learning-interpretability.
BibTeX@misc{4ortxyz_evaluating-mashap-as-a-faster-alternative-to-lime-for-model-agnostic-machine-learning-interpretability_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Evaluating MASHAP as a faster alternative to LIME for model-agnostic machine learning interpretability}}, year = {2026}, url = {https://4ort.xyz/entity/evaluating-mashap-as-a-faster-alternative-to-lime-for-model-agnostic-machine-learning-interpretability}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Evaluating MASHAP as a faster alternative to LIME for model-agnostic machine learning interpretability — https://4ort.xyz/entity/evaluating-mashap-as-a-faster-alternative-to-lime-for-model-agnostic-machine-learning-interpretability (retrieved 2026-05-24)
