arXiv Open Access 2024

Employee Turnover Analysis Using Machine Learning Algorithms

Mahyar Karimi Kamyar Seyedkazem Viliyani

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Abstrak

Employee's knowledge is an organization asset. Turnover may impose apparent and hidden costs and irreparable damages. To overcome and mitigate this risk, employee's condition should be monitored. Due to high complexity of analyzing well-being features, employee's turnover predicting can be delegated to machine learning techniques. In this paper, we discuss employee's attrition rate. Three different supervised learning algorithms comprising AdaBoost, SVM and RandomForest are used to benchmark employee attrition accuracy. Attained models can help out at establishing predictive analytics.

Topik & Kata Kunci

cs.LG

Penulis (2)

Mahyar Karimi

Kamyar Seyedkazem Viliyani

Format Sitasi

APA MLA BibTeX

Karimi, M., Viliyani, K.S. (2024). Employee Turnover Analysis Using Machine Learning Algorithms. https://arxiv.org/abs/2402.03905

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓