Abstract:Assessing the different factors that contribute to accidents in the workplace is essential to ensure the safety and well-being of employees. Given the importance of risk identification in hazard prediction, this work proposes a comparative study between different feature selection techniques (χ 2 test and Forward Feature Selection) combined with learning algorithms (Support Vector Machine, Random Forest, and Naive Bayes), both applied to a database of a leading company in the retail sector, in Portugal. The go… Show more
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