Now showing items 1-20 of 32

    • Additional feature layers from ordered aggregations for deep neural networks 

      Domínguez Catena, Iris Upna Orcid; Paternain Dallo, Daniel Upna Orcid; Galar Idoate, Mikel Upna Orcid (IEEE, 2020)   Contribución a congreso / Biltzarrerako ekarpena  OpenAccess
      In the last years we have seen huge advancements in the area of Machine Learning, specially with the use of Deep Neural Networks. One of the most relevant examples is in image classification, where convolutional neural ...
    • Addressing the overlapping data problem in classification using the one-vs-one decomposition strategy 

      Sáez, José Antonio; Galar Idoate, Mikel Upna Orcid; Krawczyk, Bartosz (IEEE, 2019)   Artículo / Artikulua  OpenAccess
      Learning good-performing classifiers from data with easily separable classes is not usually a difficult task for most of the algorithms. However, problems affecting classifier performance may arise when samples from different ...
    • Aggregation functions to combine RGB color channels in stereo matching 

      Galar Idoate, Mikel Upna Orcid; Jurío Munárriz, Aránzazu Upna Orcid; López Molina, Carlos Upna Orcid; Sanz Delgado, José Antonio Upna Orcid; Paternain Dallo, Daniel Upna Orcid; Bustince Sola, Humberto Upna Orcid (Optical Society of America, 2013)   Artículo / Artikulua  OpenAccess
      In this paper we present a comparison study between different aggregation functions for the combination of RGB color channels in stereo matching problem. We introduce color information from images to the stereo matching ...
    • Bitcoin and cybersecurity: temporal dissection of blockchain data to unveil changes in entity behavioral patterns 

      Zola, Francesco; Bruse, Jan Lukas; Eguimendia, María; Galar Idoate, Mikel Upna Orcid; Orduna Urrutia, Raúl (MDPI, 2019)   Artículo / Artikulua  OpenAccess
      The Bitcoin network not only is vulnerable to cyber-attacks but currently represents the most frequently used cryptocurrency for concealing illicit activities. Typically, Bitcoin activity is monitored by decreasing anonymity ...
    • CFM-BD: a distributed rule induction algorithm for building compact fuzzy models in Big Data classification problems 

      Elkano Ilintxeta, Mikel Upna Orcid; Sanz Delgado, José Antonio Upna Orcid; Barrenechea Tartas, Edurne Upna Orcid; Bustince Sola, Humberto Upna Orcid; Galar Idoate, Mikel Upna Orcid (IEEE, 2020)   Artículo / Artikulua  OpenAccess
      Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions and decisions. However, when it comes to ...
    • Construction of capacities from overlap indexes 

      Sanz Delgado, José Antonio Upna Orcid; Galar Idoate, Mikel Upna Orcid; Mesiar, Radko; Bustince Sola, Humberto Upna Orcid; Fernández Fernández, Francisco Javier Upna Orcid (Springer, 2017)   Capítulo de libro / Liburuen kapitulua  OpenAccess
      In this chapter, we show how the concepts of overlap function and overlap index can be used to define fuzzy measures which depend on the specific data of each considered problem.
    • d-Choquet integrals: Choquet integrals based on dissimilarities 

      Bustince Sola, Humberto Upna Orcid; Mesiar, Radko; Fernández Fernández, Francisco Javier Upna Orcid; Galar Idoate, Mikel Upna Orcid; Paternain Dallo, Daniel Upna Orcid; Altalhi, A. H.; Pereira Dimuro, Graçaliz Upna Orcid; Bedregal, Benjamin Upna; Takáč, Zdenko (Elsevier, 2020)   Artículo / Artikulua
      The paper introduces a new class of functions from [0,1]n to [0,n] called d-Choquet integrals. These functions are a generalization of the 'standard' Choquet integral obtained by replacing the difference in the definition ...
    • Dissimilarity based choquet integrals 

      Bustince Sola, Humberto Upna Orcid; Mesiar, Radko; Fernández Fernández, Francisco Javier Upna Orcid; Galar Idoate, Mikel Upna Orcid; Paternain Dallo, Daniel Upna Orcid (Springer, 2020)   Contribución a congreso / Biltzarrerako ekarpena  OpenAccess
      In this paper, in order to generalize the Choquet integral, we replace the difference between inputs in its definition by a restricted dissimilarity function and refer to the obtained function as d-Choquet integral. For ...
    • Do we still need fuzzy classifiers for Small Data in the Era of Big Data? 

      Elkano Ilintxeta, Mikel Upna Orcid; Bustince Sola, Humberto Upna Orcid; Galar Idoate, Mikel Upna Orcid (IEEE, 2019)   Contribución a congreso / Biltzarrerako ekarpena  OpenAccess
      The Era of Big Data has forced researchers to explore new distributed solutions for building fuzzy classifiers, which often introduce approximation errors or make strong assumptions to reduce computational and memory ...
    • An empirical study on supervised and unsupervised fuzzy measure construction methods in highly imbalanced classification 

      Uriz Martín, Mikel Xabier Upna; Paternain Dallo, Daniel Upna Orcid; Bustince Sola, Humberto Upna Orcid; Galar Idoate, Mikel Upna Orcid (IEEE, 2020)   Contribución a congreso / Biltzarrerako ekarpena  OpenAccess
      The design of an ensemble of classifiers involves the definition of an aggregation mechanism that produces a single response obtained from the information provided by the classifiers. A specific aggregation methodology ...
    • Enhancing multi-class classification in FARC-HD fuzzy classifier: on the synergy between n-dimensional overlap functions and decomposition strategies 

      Elkano Ilintxeta, Mikel Upna Orcid; Galar Idoate, Mikel Upna Orcid; Sanz Delgado, José Antonio Upna Orcid; Fernández, Alberto; Barrenechea Tartas, Edurne Upna Orcid; Herrera, Francisco; Bustince Sola, Humberto Upna Orcid (IEEE, 2014)   Artículo / Artikulua  OpenAccess
      There are many real-world classification problems involving multiple classes, e.g., in bioinformatics, computer vision or medicine. These problems are generally more difficult than their binary counterparts. In this scenario, ...
    • EUSC: a clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification 

      Le, Hoang Lam; Landa-Silva, Darío; Galar Idoate, Mikel Upna Orcid; García, Salvador; Triguero, Isaac (Elsevier, 2021)   Artículo / Artikulua
      Learning from imbalanced datasets is highly demanded in real-world applications and a challenge for standard classifiers that tend to be biased towards the classes with the majority of the examples. Undersampling approaches ...
    • An evolutionary underbagging approach to tackle the survival prediction of trauma patients: a case study at the Hospital of Navarre 

      Sanz Delgado, José Antonio Upna Orcid; Galar Idoate, Mikel Upna Orcid; Bustince Sola, Humberto Upna Orcid; Belzunegui Otano, Tomás Upna Orcid (IEEE, 2019)   Artículo / Artikulua  OpenAccess
      Survival prediction systems are used among emergency services at hospitals in order to measure their quality objectively. In order to do so, the estimated mortality rate given by a prediction model is compared with the ...
    • Extensions of fuzzy sets in image processing: an overview 

      Pagola Barrio, Miguel Upna Orcid; Barrenechea Tartas, Edurne Upna Orcid; Bustince Sola, Humberto Upna Orcid; Fernández Fernández, Francisco Javier Upna Orcid; Galar Idoate, Mikel Upna Orcid; Jurío Munárriz, Aránzazu Upna Orcid; López Molina, Carlos Upna Orcid; Paternain Dallo, Daniel Upna Orcid; Sanz Delgado, José Antonio Upna Orcid; Couto, P.; Melo Pinto, P. (EUSFLAT, 2011)   Artículo / Artikulua  OpenAccess
      This work presents a valuable review for the interested reader of the recent Works using extensions of fuzzy sets in image processing. The chapter is divided as follows: first we recall the basics of the extensions of fuzzy ...
    • A framework for radial data comparison and its application to fingerprint analysis 

      Marco Detchart, Cedric Upna Orcid; Cerrón González, Juan Upna; Miguel Turullols, Laura de Upna Orcid; López Molina, Carlos Upna Orcid; Bustince Sola, Humberto Upna Orcid; Galar Idoate, Mikel Upna Orcid (Elsevier, 2016)   Artículo / Artikulua  OpenAccess
      This work tackles the comparison of radial data, and proposes comparison measures that are further applied to fingerprint analysis. First, we study the similarity of scalar and non-scalar radial data, elaborated on previous ...
    • FUZZ-EQ: a data equalizer for boosting the discrimination power of fuzzy classifiers 

      Uriz Martín, Mikel Xabier Upna; Elkano Ilintxeta, Mikel Upna Orcid; Bustince Sola, Humberto Upna Orcid; Galar Idoate, Mikel Upna Orcid (Elsevier, 2020)   Artículo / Artikulua
      The definition of linguistic terms is a critical part of the construction of any fuzzy classifier. Fuzzy partitioning methods (FPMs) range from simple uniform partitioning to sophisticated optimization algorithms. In this ...
    • Fuzzy rule-based classification systems for multi-class problems using binary decomposition strategies: on the influence of n-dimensional overlap functions in the fuzzy reasoning method 

      Elkano Ilintxeta, Mikel Upna Orcid; Galar Idoate, Mikel Upna Orcid; Sanz Delgado, José Antonio Upna Orcid; Bustince Sola, Humberto Upna Orcid (Elsevier, 2016)   Artículo / Artikulua  OpenAccess
      Multi-class classification problems appear in a broad variety of real-world problems, e.g., medicine, genomics, bioinformatics, or computer vision. In this context, decomposition strategies are useful to increase the ...
    • Generative adversarial networks for bitcoin data augmentation 

      Zola, Francesco; Bruse, Jan Lukas; Etxeberria Barrio, Xabier; Galar Idoate, Mikel Upna Orcid; Orduna Urrutia, Raúl (IEEE, 2020)   Contribución a congreso / Biltzarrerako ekarpena  OpenAccess
      In Bitcoin entity classification, results are strongly conditioned by the ground-truth dataset, especially when applying supervised machine learning approaches. However, these ground-truth datasets are frequently affected ...
    • INFFC: an iterative class noise filter based on the fusion of classifiers with noise sensitivity control 

      Sáez, José Antonio; Galar Idoate, Mikel Upna Orcid; Luengo, Julián; Herrera, Francisco (Elsevier, 2015)   Artículo / Artikulua  OpenAccess
      In classification, noise may deteriorate the system performance and increase the complexity of the models built. In order to mitigate its consequences, several approaches have been proposed in the literature. Among them, ...
    • Learning channel-wise ordered aggregations in deep neural networks 

      Domínguez Catena, Iris Upna Orcid; Paternain Dallo, Daniel Upna Orcid; Galar Idoate, Mikel Upna Orcid (Springer, 2021)   Contribución a congreso / Biltzarrerako ekarpena
      One of the most common techniques for approaching image classification problems are Deep Neural Networks. These systems are capable of classifying images with different levels of detail at different levels of detail, with ...