B-PSA: A Binary Pendulum Search Algorithm for the Feature Selection Problem

Broderick Crawford, Felipe Cisternas-Caneo, Katherine Sepúlveda, Ricardo Soto, Álex Paz, Alvaro Peña, Claudio León de la Barra, Eduardo Rodriguez-Tello, Gino Astorga, Carlos Castro, Franklin Johnson, Giovanni Giachetti

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


The digitization of information and technological advancements have enabled us to gather vast amounts of data from various domains, including but not limited to medicine, commerce, and mining. Machine learning techniques use this information to improve decision-making, but they have a big problem: they are very sensitive to data variation, so it is necessary to clean them to remove irrelevant and redundant information. This removal of information is known as the Feature Selection Problem. This work presents the Pendulum Search Algorithm applied to solve the Feature Selection Problem. As the Pendulum Search Algorithm is a metaheuristic designed for continuous optimization problems, a binarization process is performed using the Two-Step Technique. Preliminary results indicate that our proposal obtains competitive results when compared to other metaheuristics extracted from the literature, solving well-known benchmarks.

Original languageEnglish
Article number249
Issue number12
Publication statusPublished - Dec 2023


  • binarization schemes
  • combinatorial optimization
  • Feature Selection Problem
  • Pendulum Search Algorithm

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications


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