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.sbu.unicamp.br/eventos/index.php/pibic/article/view/679. Acesso em: 18 mar. 2026.

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.

PDF (Inglês)
Creative Commons License
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.

Copyright (c) 2019 João Pedro Pazinato Cruz de Oliveira, Leonardo Tomazeli Duarte