Laboratorio de Investigación e Desenvolvemento en Intelixencia Artificial (LIDIA): Envíos recentes

Mostrando ítems 41-45 de 91

    • On developing an automatic threshold applied to feature selection ensembles 

      Seijo Pardo, Borja; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (Elsevier, 2019-01)
      [Abstract]: Feature selection ensemble methods are a recent approach aiming at adding diversity in sets of selected features, improving performance and obtaining more robust and stable results. However, using an ensemble ...

    • Distributed correlation-based feature selection in spark 

      Palma Mendoza, Raúl José; Marcos, Luis de; Rodríguez, Daniel; Alonso-Betanzos, Amparo (Elsevier, 2019-09)
      [Abstract]: Feature selection (FS) is a key preprocessing step in data mining. CFS (Correlation-Based Feature Selection) is an FS algorithm that has been successfully applied to classification problems in many domains. We ...

    • A scalable saliency-based feature selection method with instance-level information 

      Cancela, Brais; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo; Gama, João (Elsevier, 2019-11)
      [Abstract]: Classic feature selection techniques remove irrelevant or redundant features to achieve a subset of relevant features in compact models that are easier to interpret and so improve knowledge extraction. Most ...

    • Wavefront Marching Methods: A Unified Algorithm to Solve Eikonal and Static Hamilton-Jacobi Equations 

      Cancela, Brais; Alonso-Betanzos, Amparo (IEEE, 2019-12)
      [Abstract]: This paper presents a unified propagation method for dealing with both the classic Eikonal equation, where the motion direction does not affect the propagation, and the more general static Hamilton-Jacobi ...

    • E2E-FS: An End-to-End Feature Selection Method for Neural Networks 

      Cancela, Brais; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (IEEE, 2023-07)
      [Abstract]: Classic embedded feature selection algorithms are often divided in two large groups: tree-based algorithms and LASSO variants. Both approaches are focused in different aspects: while the tree-based algorithms ...