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Authors: Waad Bouaguel 1 ; Afef Ben Brahim 1 and Mohamed Limam 2

Affiliations: 1 University of Tunis, Tunisia ; 2 Dhofar University, Oman

ISBN: 978-989-8565-75-4

Keyword(s): Rank Aggregation, Distance Function, Filter Methods, Feature Selection, Data Dimensionality.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Computational Intelligence ; Data Analytics ; Data Engineering ; Evolutionary Computing ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Pre-Processing and Post-Processing for Data Mining ; Soft Computing ; Symbolic Systems

Abstract: Feature selection consists on selecting relevant features in order to focus the learning search. A simple and efficient setting for feature selection is to rank the features with respect to their relevance. When several rankers are applied to the same data set, their outputs are often different. Combining preference lists from those individual rankers into a single better ranking is known as rank aggregation. In this study, we develop a method to combine a set of ordered lists of feature based on an optimization function and genetic algorithm. We compare the performance of the proposed approach to that of well-known methods. Experiments show that our algorithm improves the prediction accuracy compared to single feature selection algorithms or traditional rank aggregation techniques.

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Paper citation in several formats:
Bouaguel, W.; Ben Brahim, A. and Limam, M. (2013). Feature Selection by Rank Aggregation and Genetic Algorithms.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 74-81. DOI: 10.5220/0004518700740081

@conference{kdir13,
author={Waad Bouaguel. and Afef Ben Brahim. and Mohamed Limam.},
title={Feature Selection by Rank Aggregation and Genetic Algorithms},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={74-81},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004518700740081},
isbn={978-989-8565-75-4},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - Feature Selection by Rank Aggregation and Genetic Algorithms
SN - 978-989-8565-75-4
AU - Bouaguel, W.
AU - Ben Brahim, A.
AU - Limam, M.
PY - 2013
SP - 74
EP - 81
DO - 10.5220/0004518700740081

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