Let's Predict Who Will Move to a New Job
Rania Mkhinini Gahar Adel Hidri Minyar Sassi Hidri
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.