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Authors: Jorge de la Calleja 1 ; Olac Fuentes 2 ; Jesús González 3 and Rita M. Aceves-Pérez 1

Affiliations: 1 Polytechnical University of Puebla, Mexico ; 2 University of Texas at El Paso, United States ; 3 INAOE, Mexico

Keyword(s): Machine learning, Imbalanced data sets.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Clustering and Classification Methods ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: Many real-world domains present the problem of imbalanced data sets, where examples of one class significantly outnumber examples of other classes. This situation makes learning difficult, as learning algorithms based on optimizing accuracy over all training examples will tend to classify all examples as belonging to the majority class. In this paper we introduce a method for learning from imbalanced data sets which is composed of three algorithms. Our experimental results show that our method performs accurate classification in the presence of significant class imbalance and using small training sets.

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Paper citation in several formats:
de la Calleja, J.; Fuentes, O.; González, J. and M. Aceves-Pérez, R. (2009). A LEARNING METHOD FOR IMBALANCED DATA SETS. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2009) - KDIR; ISBN 978-989-674-011-5; ISSN 2184-3228, SciTePress, pages 307-310. DOI: 10.5220/0002305303070310

@conference{kdir09,
author={Jorge {de la Calleja}. and Olac Fuentes. and Jesús González. and Rita {M. Aceves{-}Pérez}.},
title={A LEARNING METHOD FOR IMBALANCED DATA SETS},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2009) - KDIR},
year={2009},
pages={307-310},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002305303070310},
isbn={978-989-674-011-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2009) - KDIR
TI - A LEARNING METHOD FOR IMBALANCED DATA SETS
SN - 978-989-674-011-5
IS - 2184-3228
AU - de la Calleja, J.
AU - Fuentes, O.
AU - González, J.
AU - M. Aceves-Pérez, R.
PY - 2009
SP - 307
EP - 310
DO - 10.5220/0002305303070310
PB - SciTePress

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