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Authors: Matthias Reif 1 ; Annika Leveringhaus 2 ; Faisal Shafait 1 and Andreas Dengel 1

Affiliations: 1 German Research Center for Artificial Intelligence, Germany ; 2 University of Kaiserslautern, Germany

Keyword(s): Classifier Combination, Meta-learning, Meta-features, Classification, Classifier Ensembles.

Related Ontology Subjects/Areas/Topics: Classification ; Ensemble Methods ; Meta Learning ; Model Selection ; Pattern Recognition ; Theory and Methods

Abstract: Combining classifiers is a common technique in order to improve the performance and robustness of classification systems. However, the set of classifiers that should be combined is not obvious and either expert knowledge or a time consuming evaluation phase is required in order to achieve high accuracy values. In this paper, we present an approach of automatically selecting the set of base classifiers for combination. The method uses experience about previous classifier combinations and characteristics of datasets in order to create a prediction model. We evaluate the method on over 80 datasets. The results show that the presented method is able to reasonably predict a suitable set of base classifiers for most of the datasets.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Reif, M.; Leveringhaus, A.; Shafait, F. and Dengel, A. (2013). Predicting Classifier Combinations. In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-8565-41-9; ISSN 2184-4313, SciTePress, pages 293-297. DOI: 10.5220/0004266602930297

@conference{icpram13,
author={Matthias Reif. and Annika Leveringhaus. and Faisal Shafait. and Andreas Dengel.},
title={Predicting Classifier Combinations},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2013},
pages={293-297},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004266602930297},
isbn={978-989-8565-41-9},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Predicting Classifier Combinations
SN - 978-989-8565-41-9
IS - 2184-4313
AU - Reif, M.
AU - Leveringhaus, A.
AU - Shafait, F.
AU - Dengel, A.
PY - 2013
SP - 293
EP - 297
DO - 10.5220/0004266602930297
PB - SciTePress