Piza-Dávila, Hugo I.Sánchez-Díaz, GuillermoAguirre-Salado, Carlos A.Lazo-Cortés, Manuel2026-07-062026-07-062014-11Piza-Dávila, H.I., Sánchez-Díaz, G., Aguirre-Salado, C.A., Lazo-Cortés, M. A parallel hill-climbing algorithm to generate a subset of irreducible testors. Appl Intell 42, 622–641 (2015).https://hdl.handle.net/11117/12426The 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.enghttps://creativecommons.org/licenses/by-nc/4.0/deed.esPattern RecognitionHill ClimbingIrreductible TestorsFeature SelectionBinary Treesinfo:eu-repo/semantics/article