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A parallel hill-climbing algorithm to generate a subset of irreducible testors

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Abstract

The generation of irreducible testors from a training matrix is an expensive computational process: all the algorithms reported have exponential complexity. However, for some problems there is no need to generate the entire set of irreducible testors, but only a subset of them. Several approaches have been developed for this purpose, ranging from Univariate Marginal Distribution to Genetic Algorithms. This paper introduces a parallel version of a Hill-Climbing Algorithm useful to find a subset of irreducible testors from a training matrix. This algorithm was selected because it has been one of the fastest algorithms reported in the state-of-the-art on irreducible testors. In order to efficiently store every different irreducible testor found, the algorithm incorporates a digital-search tree. Several experiments with synthetic and real data are presented in this work.

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Authors and Affiliations

  1. Instituto Tecnologico y de Estudios Superiores de Occidente, Periferico Sur Manuel Gomez Morin 8585, Tlaquepaque, Jalisco, 45604, Mexico

    Ivan Piza-Davila

  2. Universidad Autonoma de San Luis Potosi, Facultad de Ingenieria, Dr. Manuel Nava 8, San Luis Potosi, SLP, 78290, Mexico

    Guillermo Sanchez-Diaz & Carlos A. Aguirre-Salado

  3. Instituto Nacional de Astrofisica, Optica y Electronica, Luis Enrique Erro no. 1, Tonantzintla, Puebla, 72840, Mexico

    Manuel S. Lazo-Cortes

Authors
  1. Ivan Piza-Davila
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  2. Guillermo Sanchez-Diaz
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  3. Carlos A. Aguirre-Salado
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  4. Manuel S. Lazo-Cortes
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Correspondence to Guillermo Sanchez-Diaz.

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Piza-Davila, I., Sanchez-Diaz, G., Aguirre-Salado, C.A. et al. A parallel hill-climbing algorithm to generate a subset of irreducible testors. Appl Intell 42, 622–641 (2015). https://doi.org/10.1007/s10489-014-0606-1

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