Let's Predict Who Will Move to a New Job

• URL: http://arxiv.org/abs/2309.08333v1
• Date: Fri, 15 Sep 2023 11:43:09 GMT
• Title: Let's Predict Who Will Move to a New Job
• Authors: Rania Mkhinini Gahar, Adel Hidri, Minyar Sassi Hidri
• Abstract summary: We discuss how machine learning is used to predict who will move to a new job. Data is pre-processed into a suitable format for ML models. Models are assessed using decision support metrics such as precision, recall, F1-Score, and accuracy.
• Score: 0.0
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: Any company's human resources department faces the challenge of predicting whether an applicant will search for a new job or stay with the company. In this paper, we discuss how machine learning (ML) is used to predict who will move to a new job. First, the data is pre-processed into a suitable format for ML models. To deal with categorical features, data encoding is applied and several MLA (ML Algorithms) are performed including Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), and eXtreme Gradient Boosting (XGBoost). To improve the performance of ML models, the synthetic minority oversampling technique (SMOTE) is used to retain them. Models are assessed using decision support metrics such as precision, recall, F1-Score, and accuracy.

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