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A novel one-vs-rest consensus learning method for crash severity prediction

Research article (Expert Systems with Applications, 2023) · cited 19× · AI/ML
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A novel one-vs-rest consensus learning method for crash severity prediction

Summary

A novel one-vs-rest consensus learning method for crash severity prediction is a scholarly article[1].

Key Facts

  • A novel one-vs-rest consensus learning method for crash severity prediction's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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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.

APA 4ort.xyz Knowledge Graph. (2026). A novel one-vs-rest consensus learning method for crash severity prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-one-vs-rest-consensus-learning-method-for-crash-severity-prediction
MLA “A novel one-vs-rest consensus learning method for crash severity prediction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-one-vs-rest-consensus-learning-method-for-crash-severity-prediction.
BibTeX @misc{4ortxyz_a-novel-one-vs-rest-consensus-learning-method-for-crash-severity-prediction_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel one-vs-rest consensus learning method for crash severity prediction}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-one-vs-rest-consensus-learning-method-for-crash-severity-prediction}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A novel one-vs-rest consensus learning method for crash severity prediction — https://4ort.xyz/entity/a-novel-one-vs-rest-consensus-learning-method-for-crash-severity-prediction (retrieved 2026-05-24)

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