Using Individual Feature Evaluation to Start Feature Subset Selection Methods for Classification

Antonio Arauzo-Azofra, José Molina-Baena, Alfonso Jiménez-Vílchez, María Luque-Rodriguez

2017

Abstract

Using a mechanism that can select the best features in a specific data set improves precision, efficiency and the adaptation capacity in a learning process and thus the resulting model as well. Normally, data sets contain more information than what is needed to generate a certain model. Due to this, many feature selection methods have been developed. Different evaluation functions and measures are applied and a selection of the best features is generated. This contribution proposes the use of individual feature evaluation methods as starting method for search based feature subset selection methods. An in-depth empirical study is carried out comparing traditional feature selection methods with the new started feature selection methods. The results show that the proposal is interesting as time gets reduced and classification accuracy gets improved.

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Paper Citation


in Harvard Style

Arauzo-Azofra A., Molina-Baena J., Jiménez-Vílchez A. and Luque-Rodriguez M. (2017). Using Individual Feature Evaluation to Start Feature Subset Selection Methods for Classification . In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 607-614. DOI: 10.5220/0006204406070614


in Bibtex Style

@conference{icaart17,
author={Antonio Arauzo-Azofra and José Molina-Baena and Alfonso Jiménez-Vílchez and María Luque-Rodriguez},
title={Using Individual Feature Evaluation to Start Feature Subset Selection Methods for Classification},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2017},
pages={607-614},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006204406070614},
isbn={978-989-758-220-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Using Individual Feature Evaluation to Start Feature Subset Selection Methods for Classification
SN - 978-989-758-220-2
AU - Arauzo-Azofra A.
AU - Molina-Baena J.
AU - Jiménez-Vílchez A.
AU - Luque-Rodriguez M.
PY - 2017
SP - 607
EP - 614
DO - 10.5220/0006204406070614