Analysis and Prediction of Employment and its factors using Machine Learning Approach

Abstract

In this article, an original study is suggested integrating with machine learning algorithms for the analysis of employability and employment. To build predictive models, researchers recommend using machine learning algorithms. To deepen their knowledge, the researchers recommend isolating the most important factors describing the model and applying other analysis techniques, such as clustering. A case study using information from the State Employability Database was carried out to assess the concept (SED). A predictive model detailing how these graduates find employment was created using project data (information on 3,600 students). The results of this case study were very positive and the authors are encouraged to improve and validate the method in follow-up surveys.