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Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study
Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study
Summary
Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study is a scholarly article[1].
Key Facts
Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study'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). Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study. Retrieved May 24, 2026, from https://4ort.xyz/entity/feasibility-of-local-interpretable-model-agnostic-explanations-lime-algorithm-as-an-effective-and-interpretable-feature-
MLA“Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/feasibility-of-local-interpretable-model-agnostic-explanations-lime-algorithm-as-an-effective-and-interpretable-feature-.
BibTeX@misc{4ortxyz_feasibility-of-local-interpretable-model-agnostic-explanations-lime-algorithm-as-an-effective-and-interpretable-feature-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study}}, year = {2026}, url = {https://4ort.xyz/entity/feasibility-of-local-interpretable-model-agnostic-explanations-lime-algorithm-as-an-effective-and-interpretable-feature-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Feasibility of local interpretable model-agnostic explanations (LIME) algorithm as an effective and interpretable feature selection method: comparative fNIRS study — https://4ort.xyz/entity/feasibility-of-local-interpretable-model-agnostic-explanations-lime-algorithm-as-an-effective-and-interpretable-feature- (retrieved 2026-05-24)
