AN HYBRID APPROACH TO FEATURE SELECTION FOR MIXED CATEGORICAL AND CONTINUOUS DATA

Gauthier Doquire, Michel Verleysen

Abstract

This paper proposes an algorithm for feature selection in the case of mixed data. It consists in ranking independently the categorical and the continuous features before recombining them according to the accuracy of a classifier. The popular mutual information criterion is used in both ranking procedures. The proposed algorithm thus avoids the use of any similarity measure between samples described by continuous and categorical attributes, which can be unadapted to many real-world problems. It is able to effectively detect the most useful features of each type and its effectiveness is experimentally demonstrated on four real-world data sets.

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Paper Citation


in Harvard Style

Doquire G. and Verleysen M. (2011). AN HYBRID APPROACH TO FEATURE SELECTION FOR MIXED CATEGORICAL AND CONTINUOUS DATA . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 386-393. DOI: 10.5220/0003634903940401


in Bibtex Style

@conference{kdir11,
author={Gauthier Doquire and Michel Verleysen},
title={AN HYBRID APPROACH TO FEATURE SELECTION FOR MIXED CATEGORICAL AND CONTINUOUS DATA},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={386-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003634903940401},
isbn={978-989-8425-79-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - AN HYBRID APPROACH TO FEATURE SELECTION FOR MIXED CATEGORICAL AND CONTINUOUS DATA
SN - 978-989-8425-79-9
AU - Doquire G.
AU - Verleysen M.
PY - 2011
SP - 386
EP - 393
DO - 10.5220/0003634903940401