An introductory study to machine learning and its application to employee turnover prediction
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Palavras-chave

Machine learning
Turnover
Extreme learning machines.

Como Citar

OLIVEIRA, João Pedro Pazinato Cruz de; DUARTE, Leonardo Tomazeli. An introductory study to machine learning and its application to employee turnover prediction. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 26, 2019. DOI: 10.20396/revpibic262018679. Disponível em: https://econtents.bc.unicamp.br/eventos/index.php/pibic/article/view/679. Acesso em: 25 abr. 2024.

Resumo

The objective of this paper is to study the problem of employee turnover prediction and to develop a classifier that uses employee's data to identify those who have a greater tendency to leave the company voluntarily. For such purpose, the data of 8724 employees from a real Brazilian beverage company was used to train an Extreme Learning Machine (ELM) classifier, assigning to each sample a weight inversely proportional to the size of the respective class. After the training, the classifier displayed an overall accuracy of 79% of the test data.

https://doi.org/10.20396/revpibic262018679
PDF (English)

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