Now showing items 1-15 of 15

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      A biobjective method for sample allocation in stratified sampling  [Article]

      Carrizosa Priego, Emilio José; Romero Morales, María Dolores (Elsevier, 2007-03-01)
      The two main and contradicting criteria guiding sampling design are accuracy of estimators and sampling costs. In stratified random sampling, the sample size must be allocated to strata in order to optimize both objectives. ...
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      A nested heuristic for parameter tuning in support vector machines  [Article]

      Carrizosa Priego, Emilio José; Martín Barragán, Belén; Romero Morales, María Dolores (Elsevier, 2014-03)
      The default approach for tuning the parameters of a Support Vector Machine (SVM) is a grid search in the parameter space. Different metaheuristics have been recently proposed as a more efficient alternative, but they have ...
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      Binarized support vector machines  [Article]

      Carrizosa Priego, Emilio José; Martín Barragán, Belén; Romero Morales, María Dolores (INFORMS (Institute for Operations Research and Management Sciences), 2010)
      The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have become more popular among practitioners than ...
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      Clustering categories in support vector machines  [Article]

      Carrizosa Priego, Emilio José; Nogales Gómez, Amaya; Romero Morales, María Dolores (Elsevier, 2016-02)
      The support vector machine (SVM) is a state-of-the-art method in supervised classification. In this paper the Cluster Support Vector Machine (CLSVM) methodology is proposed with the aim to increase the sparsity of the SVM ...
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      Detecting relevant variables and interactions in supervised classification  [Article]

      Carrizosa Priego, Emilio José; Martín Barragán, Belén; Romero Morales, María Dolores (Elsevier, 2011-08-16)
      The widely used Support Vector Machine (SVM) method has shown to yield good results in Supervised Classification problems. When the interpretability is an important issue, then classification methods such as Classification ...
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      Finding the principal points of a random variable  [Article]

      Carrizosa Priego, Emilio José; Conde Sánchez, Eduardo; Castaño Martínez, Antonia; Romero Morales, María Dolores (EDP Sciences, 2001)
      The p-principal points of a random variable X with finite second moment are those p points in R minimizing the expected squared distance from X to the closest point. Although the determination of principal points involves ...
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      Heuristic approaches for support vector machines with the ramp loss  [Article]

      Carrizosa Priego, Emilio José; Nogales Gómez, Amaya; Romero Morales, María Dolores (Springer, 2014-03)
      Recently, Support Vector Machines with the ramp loss (RLM) have attracted attention from the computational point of view. In this technical note, we propose two heuristics, the first one based on solving the continuous relaxation ...
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      Mathematical optimization for the visualization of complex datasets  [PhD Thesis]

      Guerrero Lozano, Vanesa (2017-06-26)
      This PhD dissertation focuses on developing new Mathematical Optimization models and solution approaches which help to gain insight into complex data structures arising in Information Visualization. The approaches developed ...
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      Multi-group support vector machines with measurement costs a biobjective approach  [Article]

      Carrizosa Priego, Emilio José; Martín Barragán, Belén; Romero Morales, María Dolores (Elsevier, 2008-03)
      Support Vector Machine has shown to have good performance in many practical classification settings. In this paper we propose, for multi-group classification, a biobjective optimization model in which we consider not only ...
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      Programación matemática para las máquinas de vector de apoyo: mathematical programming for support vector machines  [PhD Thesis]

      Martín Barragán, Belén (2006)
      En esta Tesis Doctoral, presentamos algunas propuestas en las que las herramientas de la Programación Matemática se usan para obtener clasificadores que tengan algunas propiedades interesantes. En aplicaciones prácticas, ...
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      Semi-obnoxious location models: a global optimization approach  [Article]

      Romero Morales, María Dolores; Carrizosa Priego, Emilio José (Elsevier, 1997-10-16)
      In the last decades there has been an increasing interest in environmental topics. This interest has been reflected in modeling the location of obnoxious facilities, as shown by the important number of papers published ...
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      Strongly agree or strongly disagree? Rating features in support vector machines  [Article]

      Carrizosa Priego, Emilio José; Nogales Gómez, Amaya; Romero Morales, María Dolores (Elsevier, 2016-02)
      In linear classifiers, such as the Support Vector Machine (SVM), a score is associated with each feature and objects are assigned to classes based on the linear combination of the scores and the values of the features. ...
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      Supervised classification and mathematical optimization  [Article]

      Carrizosa Priego, Emilio José; Romero Morales, María Dolores (Elsevier, 2013-01)
      Data Mining techniques often ask for the resolution of optimization problems. Supervised Classification, and, in particular, Support Vector Machines, can be seen as a paradigmatic instance. In this paper, some links between ...
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      Visualizing data as objects by DC (difference of convex) optimization  [Article]

      Carrizosa Priego, Emilio José; Guerrero Lozano, Vanesa; Romero Morales, María Dolores (Springer, 2017)
      In this paper we address the problem of visualizing in a bounded region a set of individuals, which has attached a dissimilarity measure and a statistical value, as convex objects. This problem, which extends the standard ...
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      Visualizing proportions and dissimilarities by space-filling maps: a large neighborhood search approach  [Article]

      Carrizosa Priego, Emilio José; Guerrero Lozano, Vanesa; Romero Morales, María Dolores (Elsevier, 2017-02)
      In this paper we address the problem of visualizing a set of individuals, which have attached a statistical value given as a proportion, and a dissimilarity measure. Each individual is represented as a region within the ...