Automated employee salary prediction algorithm based on machine learning

Shiqi Yang

doi:10.1117/12.2673738

14 April 2023 Automated employee salary prediction algorithm based on machine learning

Shiqi Yang

Proceedings Volume 12613, International Conference on Computer Vision, Application, and Algorithm (CVAA 2022); 126130Y (2023) https://doi.org/10.1117/12.2673738
Event: International Conference on Computer Vision, Application, and Algorithm (CVAA 2022), 2022, Chongqing, China

Abstract

With the Covid-19's effects on the economy, corporate earnings have decreased, and job seekers have experienced increased pressure. Individual job applicants often need to spend a considerable amount of time and energy to research and their ability to match the specific salary of the position, which is time-consuming and laborious, but also because of the collection of incomplete information and lead to wrong salary expectations. Therefore, an automated algorithm for salary evaluation is particularly important. In this paper, the salary prediction model is studied mainly from three aspects: MLP model, RF model and GBDT model, analyzing the characteristics of each model and making predictions, and finally comparing various evaluation metrics of the three models, it is concluded that the GBDT algorithm works best, and finally the GBDT algorithm is chosen to build a prediction algorithm for salary prediction. The GBDT algorithm designed for the prediction of salary can provide a reasonable and scientific reference basis for recruiters to publish job information and job seekers to search for suitable positions, which can greatly improve the success rate of recruitment and job searching.

Citation Download Citation

Shiqi Yang "Automated employee salary prediction algorithm based on machine learning", Proc. SPIE 12613, International Conference on Computer Vision, Application, and Algorithm (CVAA 2022), 126130Y (14 April 2023); https://doi.org/10.1117/12.2673738

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