AN ANALYSIS OF RANDOM FOREST MACHINE LEARNING MODELS AND ARTIFICIAL NEURAL NETWORKS

Abstract

This academic work developed an analysis using Artificial Intelligence, through machine learning techniques, with the objective of investigating how a student's social context can impact their score on the Mathematics and its Technologies test of ENEM. For this, open microdata related to the 2022 edition of ENEM were used, which include social, educational, and economic variables of the participants. These data were organized and processed with the help of machine learning algorithms, specifically Random Forest and Artificial Neural Network models, to compare the performance of each technique based on criteria such as accuracy, robustness, and interpretability. At the end of the research, the model that presented the best performance in identifying the correlation between the analyzed factors was highlighted, offering support for understanding the most influential variables and promoting a critical reflection on the role of the government in formulating public policies aimed at improving education in the country.

DOI: https://doi.org/10.56238/ERR01v10n2-004