Utilização de algoritmos de classificação para diagnóstico de diabetes

Abstract

The undergraduate thesis consists of the study of binary classification algorithms for diagnosing diabetes based on clinical data and physical activity data. For this purpose, we will accomplish a statistical and conceptual definition of the problem and obtain the results from the methods of Logistic Regression and Classification Trees. All computational applications will be done using the R programming language.