Now showing items 1-7 of 7

    • Presentation
      Icon

      Attribute Selection for Classification 

      Serendero Sáez, Santiago Patricio; Toro Bonilla, Miguel (International Association for Development of the Information Society, 2003)
      The selection of attributes used to construct a classification model is crucial in machine learning, in particular with ...
    • Presentation
      Icon

      Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals 

      Troncoso García, Ángela del Robledo; Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia (Springer Link, 2023-09)
      This paper explores the use of deep learning techniques for detecting sleep apnea. Sleep apnea is a common sleep disorder ...
    • Presentation
      Icon

      Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection 

      Jiménez Navarro, Manuel Jesús; Martínez Ballesteros, María del Mar; Sousa Brito, Isabel Sofía; Martínez Álvarez, Francisco; Asencio Cortés, Gualberto (SpringerLink, 2022)
      Neural networks have proven to be a good alternative in application fields such as healthcare, time-series forecasting and ...
    • Presentation
      Icon

      Finding Defective Modules from Highly Unbalanced Datasets 

      Riquelme Santos, José Cristóbal; Ruiz Sánchez, Roberto; Rodríguez García, Daniel; Moreno, J. (Sociedad de Ingeniería de Software y Tecnologías de Desarrollo de Software (SISTEDES), 2008-10)
      Many software engineering datasets are highly unbalanced, i.e., the number of instances of a one class outnumber the number ...
    • Presentation
      Icon

      Low Dimensionality or Same Subsets as a Result of Feature Selection: An In-Depth Roadma 

      Tallón Ballesteros, Antonio Javier; Riquelme Santos, José Cristóbal (Springer, 2017-06)
      This paper addresses the situation that may happen after the application of feature subset selection in terms of a reduced ...
    • Presentation
      Icon

      On the performance of deep learning models for time series classification in streaming 

      Lara Benítez, Pedro; Carranza García, Manuel; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (Springer, 2020)
      Processing data streams arriving at high speed requires the development of models that can provide fast and accurate ...
    • Presentation
      Icon

      SmartFD: A Real Big Data Application for Electrical Fraud Detection 

      Gutiérrez Avilés, David; Fábregas, J. A.; Tejedor, Javier; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Arcos Vargas, Ángel; Riquelme Santos, José Cristóbal (Springer, 2018)
      The main objective of this paper is the application of big data analytics to a real case in the field of smart electric ...