On the Improvement of Feature Selection Techniques: The Fitness Filter

Artur Ferreira, Artur Ferreira, Mário Figueiredo, Mário Figueiredo

2021

Abstract

The need for feature selection (FS) techniques is central in many machine learning and pattern recognition problems. FS is a vast research field and therefore we now have many FS techniques proposed in the literature, applied in the context of quite different problems. Some of these FS techniques follow the relevance-redundancy (RR) framework to select the best subset of features. In this paper, we propose a supervised filter FS technique, named as fitness filter, that follows the RR framework and uses data discretization. This technique can be used directly on low or medium dimensional data or it can be applied as a post-processing technique to other FS techniques. Specifically, when used as a post-processing technique, it further reduces the dimensionality of the feature space found by common FS techniques and often improves the classification accuracy.

Paper Citation

in Harvard Style

Ferreira A. and Figueiredo M. (2021). On the Improvement of Feature Selection Techniques: The Fitness Filter.In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 365-372. DOI: 10.5220/0010396303650372

in Bibtex Style

@conference{icpram21,
author={Artur Ferreira and Mário Figueiredo},
title={On the Improvement of Feature Selection Techniques: The Fitness Filter},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2021},
pages={365-372},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010396303650372},
isbn={978-989-758-486-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - On the Improvement of Feature Selection Techniques: The Fitness Filter
SN - 978-989-758-486-2
AU - Ferreira A.
AU - Figueiredo M.
PY - 2021
SP - 365
EP - 372
DO - 10.5220/0010396303650372