B-PSA: A Binary Pendulum Search Algorithm for the Feature Selection Problem
Abstract
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.
Más información
Título según WOS: | ID WOS:001135930600001 Not found in local WOS DB |
Título según SCOPUS: | ID SCOPUS_ID:85180641619 Not found in local SCOPUS DB |
Título de la Revista: | computers |
Volumen: | 12 |
Editorial: | MDPI |
Fecha de publicación: | 2023 |
Página de inicio: | 249 |
DOI: |
10.3390/COMPUTERS12120249 |
Notas: | ISI, SCOPUS - ISI-WOS |