Home ›
Entities
› academia
› Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion
Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion
Research article (Applied Sciences, 2021) · cited 41× · AI/ML
Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion
Summary
Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion is a scholarly article[1].
Key Facts
Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion. Retrieved May 24, 2026, from https://4ort.xyz/entity/towards-a-more-reliable-interpretation-of-machine-learning-outputs-for-safety-critical-systems-using-feature-importance-
MLA“Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/towards-a-more-reliable-interpretation-of-machine-learning-outputs-for-safety-critical-systems-using-feature-importance-.
BibTeX@misc{4ortxyz_towards-a-more-reliable-interpretation-of-machine-learning-outputs-for-safety-critical-systems-using-feature-importance-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion}}, year = {2026}, url = {https://4ort.xyz/entity/towards-a-more-reliable-interpretation-of-machine-learning-outputs-for-safety-critical-systems-using-feature-importance-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems Using Feature Importance Fusion — https://4ort.xyz/entity/towards-a-more-reliable-interpretation-of-machine-learning-outputs-for-safety-critical-systems-using-feature-importance- (retrieved 2026-05-24)
