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Authors: Mariam Kalakech 1 ; Philippe Biela 2 ; Denis Hamad 3 and Ludovic Macaire 4

Affiliations: 1 HEI and Université Lille 1, France ; 2 HEI, France ; 3 LISIC and ULCO, France ; 4 Université Lille 1, France

ISBN: 978-989-8425-84-3

Keyword(s): Feature selection, Constraint scores, Pairwise constraints, Semi-supervised evaluation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Supervised and Unsupervised Learning ; Theory and Methods

Abstract: Recent feature constraint scores, that analyse must-link and cannot-link constraints between learning samples, reach good performances for semi-supervised feature selection. The performance evaluation is generally based on classification accuracy and is performed in a supervised learning context. In this paper, we propose a semi-supervised performance evaluation procedure, so that both feature selection and classification take into account the constraints given by the user. Extensive experiments on benchmark datasets are carried out in the last section. They demonstrate the effectiveness of feature selection based on constraint analysis.

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Paper citation in several formats:
Kalakech, M.; Biela, P.; Hamad, D. and Macaire, L. (2011). SEMI-SUPERVISED EVALUATION OF CONSTRAINT SCORES FOR FEATURE SELECTION.In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 175-182. DOI: 10.5220/0003680001750182

@conference{ncta11,
author={Mariam Kalakech. and Philippe Biela. and Denis Hamad. and Ludovic Macaire.},
title={SEMI-SUPERVISED EVALUATION OF CONSTRAINT SCORES FOR FEATURE SELECTION},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)},
year={2011},
pages={175-182},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003680001750182},
isbn={978-989-8425-84-3},
}

TY - CONF

JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)
TI - SEMI-SUPERVISED EVALUATION OF CONSTRAINT SCORES FOR FEATURE SELECTION
SN - 978-989-8425-84-3
AU - Kalakech, M.
AU - Biela, P.
AU - Hamad, D.
AU - Macaire, L.
PY - 2011
SP - 175
EP - 182
DO - 10.5220/0003680001750182

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