Listar por autor "Gutiérrez, Pedro A."

Mostrando ítems 1-10 de 10

    • A Review of Classification Problems and Algorithms in Renewable Energy Applications 

      Pérez-Ortiz, María; Jiménez-Fernández, Silvia; Gutiérrez, Pedro A.; Alexandre, Enrique; Salcedo Sanz, S.; Hervás-Martínez, César (MDPI, 2016)
      Classification problems and their corresponding solving approaches constitute one of the fields of machine learning. The application of classification schemes in Renewable Energy (RE) has gained significant attention in ...

    • Algoritmos de aprendizaje evolutivo y estadístico para la determinación de mapas de malas hierbas utilizando técnicas de teledetección 

      Gutiérrez, Pedro A.; Fernández, J.C.; Hervás-Martínez, César (2013-10-08)
      Este trabajo aborda la resolución de problemas de clasificación binaria utilizando una metodología híbrida que combina la regresión logística y modelos evolutivos de redes neuronales de unidades producto. Para estimar ...

    • Borderline kernel based over-sampling 

      Pérez-Ortiz, María; Gutiérrez, Pedro A.; Hervás-Martínez, César (2017-03-30)
      Nowadays, the imbalanced nature of some real-world data is receiving a lot of attention from the pattern recognition and machine learning communities in both theoretical and practical aspects, giving rise to di erent ...

    • Exploitation of Pairwise Class Distances for Ordinal Classification 

      Sánchez-Monedero, J.; Gutiérrez, Pedro A.; Tino, Peter; Hervás-Martínez, César (2013-07-15)
      Ordinal classification refers to classification problems in which the classes have a natural order imposed on them because of the nature of the concept studied. Some ordinal classification approaches perform a projection ...

    • Ordinal Prediction using machine learning methodologies: Applications 

      Dorado Moreno, Manuel (Universidad de Córdoba, UCOPress, 2019)
      Artificial Intelligence is part of our everyday life, not only as consumers but also in most of the productive areas since companies can optimize most of their processes with all the different tools that it can provide. ...

    • Ordinal regression methods: survey and experimental study 

      Gutiérrez, Pedro A.; Pérez-Ortiz, María; Sánchez-Monedero, J.; Fernández-Navarro, Francisco; Hervás-Martínez, César (2017-02-03)
      Abstract—Ordinal regression problems are those machine learning problems where the objective is to classify patterns using a categorical scale which shows a natural order between the labels. Many real-world applications ...

    • Projection based ensemble learning for ordinal regression 

      Pérez-Ortiz, María; Gutiérrez, Pedro A.; Hervás-Martínez, César (2013-10-08)
      The classification of patterns into naturally ordered labels is referred to as ordinal regression. This paper proposes an ensemble methodology specifically adapted to this type of problems, which is based on computing ...

    • Regresión no lineal mediante la evolución de modelos Híbridos de Redes Neuronales 

      Martínez, Francisco J.; Gutiérrez, Pedro A.; Ruiz, Aarón; Hervás-Martínez, César (Comité Organizador de MAEB'05, 2005)
      El presente trabajo es una primera aproximación a la formación de modelos de redes neuronales con unidades ocultas de tipo híbrido (sigmoides, producto) que siendo aproximadores universales, puedan utilizarse como ...

    • Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery 

      Pérez-Ortiz, María; Gutiérrez, Pedro A.; Torres-Sánchez, Jorge; Hervás-Martínez, César; López-Granados, Francisca; Peña, José Manuel (2017-03-30)
      This paper approaches the problem of weed mapping for precision agriculture, using imagery provided by Unmanned Aerial Vehicles (UAVs) from sun ower and maize crops. Precision agriculture referred to weed control is ...

    • Time series data mining: preprocessing, analysis, segmentation and prediction. Applications 

      Durán Rosal, Antonio Manuel (Universidad de Córdoba, UCOPress, 2019)
      Currently, the amount of data which is produced for any information system is increasing exponentially. This motivates the development of automatic techniques to process and mine these data correctly. Specifically, in this ...