Analyzing Predictors of Schools’ Performance using Machine Learning Methods: Case of Primary and Secondary Schools in Slovakia
This thesis explores the determinants of educational performance in Slovak schools using advanced machine-learning (ML) techniques. It identifies key factors influencing academic outcomes and evaluates the effectiveness of various ML models, including Random Forest, Gradient Boosting, and Neural Networks, among others. This study compiled a complex dataset of 1409 primary and 656 secondary schools