Machine Learning for Liability Attribution in Pedestrians Involved in Traffic Crashes: Interpretability and Class Imbalance Solutions
This paper proposes a Machine Learning (ML) framework designed to attribute liability between drivers and pedestrians in traffic crashes. This study applies classification algorithms and interpretability techniques to analyze judicial rulings related to pedestrian crashes in Badajoz, Spain, from 201...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
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MDPI AG
2026-07-01
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| Serie: | Mathematics |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2227-7390/14/13/2389 |
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