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Redes neurais aplicadas a grafos: uma abordagem semi-supervisionada
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 18/04/2022)In this work, we propose an in-depth analysis of Graph Convolutional Networks, a semi-supervised machine learning method for node classification in graph-structured data. Based on the seminal work proposed by Thomas Kipf ... -
Seleção de marcadores SNP: uma aplicação com diferentes metodologias
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 25/09/2020)The quantity and complexity of generated data due to advances in genetic sequencing technologies has made statistical analysis an essential tool for their correct study and interpretation. However, there is still no agreement ... -
Seleção de variáveis: uma aplicação a dados de moinho de cimento
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 07/12/2019)Having as object of study a certain mill that produces cement, we use two methods of variable selection, LASSO and stepwise, to identify variables that influence the engine power and, consequently, impact the cement ... -
Seleção estatística de árvores de contexto
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 22/01/2024)Context trees are models that parsimoniously generalize Markovian models. These models were introduced by Jorma Rissanen in 1983, as an efficient tool in Information Theory. Since then, these models have been widely used ... -
Utilização de algoritmos de classificação para diagnóstico de diabetes
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 15/02/2024)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 ... -
Utilização de métodos de aprendizado de máquina para estimação de escores de propensão
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 18/04/2022)Increasingly larger and more complex databases can be easily obtained and appropriate technologies for modeling massive amounts of data become increasingly necessary in order to optimize results and predictions. Machine ...