Improved ACO Rank-Based Algorithm for Use in Selecting Features for Classification Models

Roberto Delamora, Roberto Delamora, Bruno Coelho, Jodelson Sabino

2023

Abstract

Attribute selection is a process by which the best subset of attributes in a given dataset is searched. In a world where decisions are increasingly based on data, it is essential to develop tools that allow this selection of attributes to be more efficiently performed, aiming to improve the final performance of the models. Ant colony optimization (ACO) is a well-known metaheuristic algorithm with several applications and recent versions developed for feature selection (FS). In this work, we propose an improvement in the general construction of ACO, with improvements and adjustments for subset evaluation in the original Rank-based version by BulInheimer et al. to increase overall efficiency. The proposed approach was evaluated on several real-life datasets taken from the UCI machine-learning repository, using various classifier models. The experimental results were compared with the recently published WFACOFS method by Ghosh et al., which shows that our method outperforms WFACOFS in most cases.

Paper Citation

in Harvard Style

Delamora R., Coelho B. and Sabino J. (2023). Improved ACO Rank-Based Algorithm for Use in Selecting Features for Classification Models. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-648-4, SciTePress, pages 291-302. DOI: 10.5220/0011725300003467

in Bibtex Style

@conference{iceis23,
author={Roberto Delamora and Bruno Coelho and Jodelson Sabino},
title={Improved ACO Rank-Based Algorithm for Use in Selecting Features for Classification Models},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2023},
pages={291-302},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011725300003467},
isbn={978-989-758-648-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Improved ACO Rank-Based Algorithm for Use in Selecting Features for Classification Models
SN - 978-989-758-648-4
AU - Delamora R.
AU - Coelho B.
AU - Sabino J.
PY - 2023
SP - 291
EP - 302
DO - 10.5220/0011725300003467
PB - SciTePress