Now showing items 1-20 of 73

    • A first approximation in order to define a Difficulty Factor of the bi-classification in a dataset by using SVMs 

      González Abril, Luis; Angulo Bahón, Cecilio (2013)
      Conference lecture
      Open Access
      The main aim in this paper is to analyze the complexity of a Support Vector Machine -SVM- in the construction of a classifier for a bi-classification problem on a specific dataset. Hence, an index is defined in terms of ...
    • A multi-scale smoothing kernel for measuring time-series similarity 

      Troncoso, Alicia; Arias Vicente, Marta; Riquelme Santos, José Cristóbal (2015-11-01)
      Article
      Open Access
      In this paper a kernel for time-series data is introduced so that it can be used for any data mining task that relies on a similarity or distance metric. The main idea of our kernel is that it should recognize as highly ...
    • A post-processing strategy for SVM learning from unbalanced data 

      Núñez Castro, Haydemar; González Abril, Luis; Angulo Bahón, Cecilio (2011)
      Conference lecture
      Open Access
      Standard learning algorithms may perform poorly when learning from unbalanced datasets. Based on the Fisher’s discriminant analysis, a post-processing strategy is introduced to deal datasets with significant imbalance ...
    • A probabilistic tri-class Support Vector Machine 

      González Abril, Luis; Angulo Bahón, Cecilio; Velasco Morente, Francisco; Ortega Ramírez, Juan Antonio (2010-07)
      Article
      Open Access
      A probabilistic interpretation for the output obtained from a tri-class Support Vector Machine into a multi-classification problem is presented in this paper. Probabilistic outputs are defined when solving a multi-class ...
    • A study on output normalization in multiclass SVMs 

      González Abril, Luis; Velasco Morente, Francisco; Angulo Bahón, Cecilio; Ortega Ramírez, Juan Antonio (2013-02-01)
      Article
      Restricted access - publisher's policy
      The use of binary support vector machines (SVMs) in multi-classification is addressed in this paper. Margins associated to the bi-classifiers, since they depend on the geometrical disposition of the classes being separated, ...
    • An empirical comparison of machine learning techniques for dam behaviour modelling 

      Salazar González, Fernando; Toledo Municio, Miguel Ángel; Oñate Ibáñez de Navarra, Eugenio; Morán Moya, Rafael (2015-09)
      Article
      Open Access
      Predictive models are essential in dam safety assessment. Both deterministic and statistical models applied in the day-to-day practice have demonstrated to be useful, although they show relevant limitations at the same ...
    • An investigation into new kernels for categorical variables 

      Villegas García, Marco Antonio (Universitat Politècnica de Catalunya, 2013-01)
      Master thesis
      Open Access
      Kernel-based methods first appeared in the form of support vector machines. Since the first Support Vector Machine (SVM) formulation in 1995, we have seen how the number of proposed kernel functions has quickly grown, ...
    • Analysis on distance metrics approaches in graphs and their applications 

      Cebollero Ruiz, Laura (Universitat Politècnica de Catalunya, 2019-07-05)
      Master thesis
      Restricted access - confidentiality agreement
    • Analyzing human gait and posture by combining feature selection and kernel methods 

      Samà Monsonís, Albert; Angulo Bahón, Cecilio; Pardo Ayala, Diego Esteban; Català Mallofré, Andreu; Cabestany Moncusí, Joan (2011-09)
      Article
      Open Access
      This paper evaluates a set of computational algorithms for the automatic estimation of human postures and gait properties from signals provided by an inertial body sensor. The use of a single sensor device imposes ...
    • AoL: Action Learning: A methodology to capture expertise in adjustment tasks 

      Ruiz Vegas, Francisco Javier; Samà Monsonís, Albert; Raya Giner, Cristóbal; Agell Jané, Núria (2012)
      Conference report
      Open Access
      It is well known that some people can perform a task with greater precision and accuracy than others: they are experts. In the past, experts were interviewed to find out why they have this expertise, but this was not ...
    • Assessing motor fluctuations in Parkinson’s disease patients based on a single inertial sensor 

      Pérez López, Carlos; Samà Monsonís, Albert; Rodríguez Martín, Daniel Manuel; Català Mallofré, Andreu; Cabestany Moncusí, Joan; Moreno Aróstegui, Juan Manuel; De Mingo Fernandez, Eva; Rodríguez Molinero, Alejandro (2016-12-15)
      Article
      Open Access
      Altered movement control is typically the first noticeable symptom manifested by Parkinson’s disease (PD) patients. Once under treatment, the effect of the medication is very patent and patients often recover correct ...
    • Averaging of kernel functions 

      Belanche Muñoz, Luis Antonio; Tosi, Alessandra (2012)
      Conference report
      Open Access
      In kernel-based machines, the integration of several kernels to build more flexible learning methods is a promising avenue for research. In particular, in Multiple Kernel Learning a compound kernel is build by learning a ...
    • Bi-Gaussian score equalization in an audio-visual SVM-based person verification system 

      Ejarque, Pascual; Hernando Pericás, Francisco Javier (2008)
      Conference report
      Open Access
      In multimodal fusion systems a normalization of the features or the scores is needed before the fusion process. In this work, in addition to the conventional methods, histogram equalization, which was recently introduced ...
    • Cardiovascular coupling-based classification of ischemic and dilated cardiomyopathy patients 

      Rodríguez Benítez, Javier; Schulz, Steffen; Voss, Andreas; Giraldo Giraldo, Beatriz (Institute of Electrical and Electronics Engineers (IEEE), 2019)
      Conference lecture
      Open Access
      Cardiovascular diseases are one of the most common causes of death in elderly patients. The etiology of cardiomyopathies is difficult to discern clinically. The objective of this study was to classify cardiomyopathy patients ...
    • Characterization and classification of patients with different levels of cardiac death risk by using Poincaré plot analysis 

      Rodríguez Benítez, Javier; Voss, Andreas; Caminal Magrans, Pere; Bayés Genis, Antoni; Giraldo Giraldo, Beatriz (2017)
      Conference lecture
      Open Access
      Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using ...
    • Characterization of damage evolution on metallic components using ultrasonic non-destructive methods 

      Piñal Moctezuma, Juan Fernando (Universitat Politècnica de Catalunya, 2019-09-27)
      Doctoral thesis
      Open Access
      When fatigue is considered, it is expected that structures and machinery eventually fail. Still, when this damage is unexpected, besides of the negative economic impact that it produces, life of people could be potentially ...
    • Classification of acoustic events using SVM-based clustering schemes 

      Temko, Andrey A.; Nadeu Camprubí, Climent (2006)
      Article
      Open Access
      Acoustic events produced in controlled environments may carry information useful for perceptually aware interfaces. In this paper we focus on the problem of classifying 16 types of meeting-room acoustic events. First of ...
    • Comparing error minimized extreme learning machines and support vector sequential feed-forward neural networks 

      Romero Merino, Enrique; Alquézar Mancho, René (2010-06)
      Research report
      Open Access
      Recently, error minimized extreme learning machines (EM-ELMs) have been proposed as a simple and efficient approach to build single-hidden-layer feed-forward networks (SLFNs) sequentially. They add random hidden nodes one ...
    • Comparing error minimized extreme learning machines and support vector sequential feed-forward neural networks 

      Romero Merino, Enrique; Alquézar Mancho, René (2012-01)
      Article
      Restricted access - publisher's policy
      Recently, error minimized extreme learning machines (EM-ELMs) have been proposed as a simple and efficient approach to build single-hidden-layer feed-forward networks (SLFNs) sequentially. They add random hidden nodes one ...
    • Damage diagnosis for offshore wind turbine foundations based on the fractal dimension 

      Hoxha, Ervin; Vidal Seguí, Yolanda; Pozo Montero, Francesc (2020-10-05)
      Article
      Open Access
      Cost-competitiveness of offshore wind depends heavily in its capacity to switch preventive maintenance to condition-based maintenance. That is, to monitor the actual condition of the wind turbine (WT) to decide when and ...