Browsing by Subject "Dimensionality reduction"

Now showing items 1-4 of 4

    • A Study of the ISOMAP Algorithm and Its Applications in Machine Learning 

      David, Lucas Oliveira (Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 11/12/2015)
      This project aims to study the foundations of nonlinear dimensionality reduction through manifold learning with the algorithm known as Isometric Feature Mapping (ISOMAP) and observe the application of the algorithm in ...

    • Neural networks for feature-extraction in multi-target classification 

      Cambuí, Brendon Gouveia (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 21/08/2020)
      Multi-target learning is a prediction task where each data example is associated with multiple target-variables (outputs) simultaneously. One of the challenges in this research field is related to the high dimensionality ...

    • Uma análise de regressão logística usando componentes principais 

      Goes, Gustavo Ramos de (Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 25/01/2024)
      In this Bachelors dissertation we studied, in the context of logistic regression models, the case in which the number of covariables is large and the covariables are correlated. In this situation, we use the principal ...

    • Dimensionality reduction-based metric learning using information theoretic measures 

      Cervati Neto, Alaor (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 30/04/2024)
      Processing large amounts of data to extract useful information is one of the main issues that may be approached using machine learning. One way to obtain this information is by grouping data according to their common ...