A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns

  1. Angel Miguel Garcia-Vico 1
  2. Carmona, Cristobal J. 1
  3. Pedro Gonzalez 1
  4. Jesus, Maria Jose del 1
  1. 1 Universidad de Jaén
    info

    Universidad de Jaén

    Jaén, España

    ROR https://ror.org/0122p5f64

Libro:
15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020
  1. Álvaro Herrero (coord.)
  2. Carlos Cambra (coord.)
  3. Daniel Urda (coord.)
  4. Javier Sedano (coord.)
  5. Héctor Quintián (coord.)
  6. Emilio Corchado (coord.)

Editorial: Springer Suiza

ISBN: 978-3-030-57801-5,  978-3-030-57802-2

Año de publicación: 2021

Páginas: 100-110

Congreso: International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO (15. 2020. Burgos)

Tipo: Aportación congreso

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Resumen

A preliminary many objective algorithm for extracting fuzzy emerging patterns is presented in this contribution. The proposed algorithm employs fuzzy logic together with an evolutionary algorithm. The aim is to expand the complex search space that we have in emerging pattern mining.The experimental study presented in this paper faces this new proposal regarding an ensemble of one of the most used algorithms within supervised descriptive rule discovery. Results presents a set of patterns with a major interpretability and precision for the new proposal which could be interesting for experts in real-world applications.

Fuente de los datos: Dialnet