• JCLEC Meets WEKA! 

      Cano, Alberto; Luna, J.M.; Olmo Ortiz, Juan Luis; Ventura Soto, S. (2014-02-27)
      WEKA has recently become a very referenced DM tool. In spite of all the functionality it provides, it does not include any framework for the development of evolutionary algorithms. An evolutionary computation framework ...
    • JCLEC-MO: A Java suite for solving many-objective optimization engineering problems 

      Ramírez, Aurora; Romero, José Raúl; García-Martínez, Carlos; Ventura Soto, S. (Elsevier, 2019)
      Although metaheuristics have been widely recognized as efficient techniques to solve real-world optimization problems, implementing them from scratch remains difficult for domain-specific experts without programming skills. ...
    • Jewelry Recognition via Encoder-Decoder Models 

      Alcalde-Llergo, José M.; Yeguas-Bolívar, Enrique; Zingoni, Andrea; Fuerte-Jurado, Alejandro (IEEE, 2023)
      Jewelry recognition is a complex task due to the different styles and designs of accessories. Precise descriptions of the various accessories is something that today can only be achieved by experts in the field of ...
    • Keypoint descriptor fusion with Dempster-Shafer Theory 

      Mondéjar Guerra, Víctor Manuel; Muñoz-Salinas, Rafael; Marín-Jiménez, M.J.; Carmona Poyato, Ángel; Medina-Carnicer, R. (2017)
      Keypoint matching is the task of accurately nding the location of a scene point in two images. Many keypoint descriptors have been proposed in the literature aiming at providing robustness against scale, translation and ...
    • LAIM discretization for multi-label data 

      Cano, Alberto; Luna, J.M.; Gibaja, Eva; Ventura Soto, S. (2017)
      Multi-label learning is a challenging task in data mining which has attracted growing attention in recent years. Despite the fact that many multi-label datasets have continuous features, general algorithms developed specially ...
    • Librería para el procesamiento de señales digitales con computadora 

      Fernández García, Nicolás Luis; Carmona Poyato, Ángel; Medina-Carnicer, R. (Universidad de Córdoba, Vicerrectorado de Innovación y Calidad Docente, 2004)
      In this work the basic characteristics of the development and the functionality of a specific software are exposed for the teaching in any matter that includes among their contents the "digital signal processing". The ...
    • Local-based k values for multi-label k-nearest neighbors rule 

      Romero-del-Castillo, Juan A.; Mendoza-Hurtado, Manuel; Ortiz-Boyer, Domingo; García Pedrajas, Nicolás (Elsevier, 2022)
      Multi-label learning is a growing field in machine learning research. Many applications address instances that simultaneously belong to many categories, which cannot be disregarded if optimal results are desired. Among the ...
    • Measuring Spinal Mobility Using an Inertial Measurement Unit System: A Validation Study in Axial Spondyloarthritis 

      Aranda-Valera, I. Concepción; Cuesta-Vargas, Antonio; Garrido Castro, Juan Luis; Gardiner, Philip V.; López Medina, Eloísa Clementina; Machado, Pedro M.; Condell, Joan; Connolly, James; Williams, Jonathan M.; Muñoz-Esquivel, Karla; O’Dwyer, Tom; Castro Villegas, María del Carmen; González-Navas, Cristina; Collantes Estévez, Eduardo; iMaxSpA Study Group (MDPI, 2020)
      Portable inertial measurement units (IMUs) are beginning to be used in human motion analysis. These devices can be useful for the evaluation of spinal mobility in individuals with axial spondyloarthritis (axSpA). The ...
    • Melanoma Recognition by Fusing Convolutional Blocks and Dynamic Routing between Capsules 

      Pérez, Eduardo; Ventura Soto, S. (MDPI, 2021)
      Skin cancer is one of the most common types of cancers in the world, with melanoma being the most lethal form. Automatic melanoma diagnosis from skin images has recently gained attention within the machine learning community, ...
    • Memetic Evolutionary Multi-Objective Neural Network Classifier to Predict Graft Survival in Liver Transplant Patients 

      Cruz-Ramírez, M.; Fernández, Juan Carlos; Fernández-Navarro, F.; Briceño Delgado, Francisco Javier; Mata García, Manuel de la; Hervás-Martínez, César (2017-02-17)
      In liver transplantation, matching donor and recipient is a problem that can be solved using machine learning techniques. In this paper we consider a liver transplant dataset obtained from eleven Spanish hospitals, ...
    • Memetic Pareto Evolutionary Artificial Neural Networks for the determination of growth limits of Listeria Monocytogenes 

      Fernández, J.C.; Gutiérrez, P.A.; Hervás-Martínez, César; Martínez, Francisco J. (2015-10-08)
      The main objective of this work is to automatically design neural network models with sigmoidal basis units for classification tasks, so that classifiers are obtained in the most balanced way possible in terms of CCR ...
    • MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning 

      Belmonte Pérez, Álvaro Andrés; Zafra, Amelia; Gibaja, Eva (Elsevier, 2022)
      MIML library is a Java software tool to develop, test, and compare classification algorithms for multi-instance multi-label (MIML) learning. The library includes 43 algorithms and provides a specific format and facilities ...
    • Minería de datos educativos para la detección de recursos clave 

      Gibaja, Eva; Zafra Gómez, Amelia; Luque Rodríguez, María; Arauzo Azofra, Antonio; Ramírez Quesada, Aurora; Olmo Ortiz, Juan Luis (UCOPress, 2017)
      Este artículo describe un proyecto de innovación educativa centrado en diseñar y desarrollar un nuevo módulo de Moodle que permita obtener modelos predictivos basados en árboles de decisión a partir de los datos de uso ...
    • Mixing body-parts model for 2D human pose estimation in stereo videos 

      López-Quintero, Manuel I.; Marín-Jiménez, M.J.; Muñoz-Salinas, Rafael; Medina-Carnicer, R. (Institution of Engineering and Technology, 2017)
      This study targets 2D articulated human pose estimation (i.e. localisation of body limbs) in stereo videos. Although in recent years depth-based devices (e.g. Microsoft Kinect) have gained popularity, as they perform very ...
    • ML-k’sNN: Label Dependent k Values for Multi-Label k-Nearest Neighbor Rule 

      Cuevas-Muñoz, José Manuel; García Pedrajas, Nicolás (MDPI, 2023)
      Multi-label classification as a data mining task has recently attracted increasing interest from researchers. Many current data mining applications address problems with instances that belong to more than one category. ...
    • Modeling and predicting students’ engagement behaviors using mixture Markov models 

      Maqsood, Rabia; Ceravolo, Paolo; Romero Morales, C.; Ventura Soto, S. (Springer, 2022)
      Students’ engagements reflect their level of involvement in an ongoing learning processwhich can be estimated through their interactions with a computer-based learning or assessment system. A pre-requirement for stimulating ...
    • Modelo de asignación donante-receptor español en transplantes hepáticos 

      Briceño Delgado, Francisco Javier; Mata García, Manuel de la; Cruz Ramírez, Manuel; Hervás-Martínez, César (Consejo Social de la Universidad de Córdoba, 2011)
      El reto que presentan los autores del proyecto se centra en encontrar un modelo español de asignación donante-receptor en trasplantes de hígado que sea válido a un número de pares donantes-receptores. El método que proponen ...
    • Multi-Objective Genetic Programming for Feature Extraction and Data Visualization 

      Cano, Alberto; Ventura Soto, S.; Cios, Krzyztof J. (2017)
      Feature extraction transforms high dimensional data into a new subspace of lower dimensionalitywhile keeping the classification accuracy. Traditional algorithms do not consider the multi-objective nature of this task. ...
    • Multi-source and multimodal data fusion for predicting academic performance in blended learning university courses 

      Chango, Wilson; Cerezo, Rebeca; Romero Morales, C. (Elsevier, 2021)
      In this paper we apply data fusion approaches for predicting the final academic performance of university students using multiple-source, multimodal data from blended learning environments. We collect and preprocess data ...
    • Multi-view gait recognition on curved 

      López-Fernández, D.; Madrid-Cuevas, F.J.; Carmona Poyato, Ángel; Muñoz-Salinas, Rafael; Medina-Carnicer, R. (2017-12-11)
      Appearance changes due to viewing angle changes cause difficulties for most of the gait recognition methods. In this paper, we propose a new approach for multi-view recognition, which allows to recognize people walking on ...