Feature Selection using LAID and its Implementation on High-Performance Computing Systems

• Autor(a) principal: Morgado, Paulo
• Data de Publicação: 2021
• Outros Autores: Cavique, Luís
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.34627/rcc.v16i0.266

From the set of dimensionality reduction techniques, we focus on the feature selection, a possible approach to carry it out is the use of Logical Analysis of Inconsistent Data (LAID). Recently, studies have demonstrated its potential in solving this problem and highlighted its advantages as a robust methodology, easy to interpret, and additionally capable of dealing with inconsistent data. The same studies revealed processing times higher than desired for full use and recommended the execution of algorithms through parallel processing using high-performance computing (HPC). This work represents yet another contribution to this effort by addressing ways of storing data, solutions for parallelizing algorithms, configuring the HPC environment, and finally testing the National Infrastructure for Distributed Computing (INCD) that allowed us to draw the conclusions presented.