---
title: Predicting Work Accidents with ML
url: https://www.ml-quant.com/papers/ssrn/5259984/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5259984
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5259984
featured: 2025-05-21
citations: unknown
topic: ML & AI Methods
---


# Predicting Work Accidents with ML

The study assesses the effectiveness of dimensionality reduction methods in predicting occupational accidents in retail, finding that Forward Feature Selection combined with the Gradient Boosting Classifier is most effective.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5259984
- Identifier: SSRN 5259984
- Released: 2025-05-19
- First featured: Quant Letter No. 98 (2025-05-21): https://www.ml-quant.com/issues/2025-05-21/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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