oAdaBoost - An AdaBoost Variant for Ordinal Classification

João Costa, Jaime S. Cardoso

2015

Abstract

Ordinal data classification (ODC) has a wide range of applications in areas where human evaluation plays an important role, ranging from psychology and medicine to information retrieval. In ODC the output variable has a natural order; however, there is not a precise notion of the distance between classes. The Data Replication Method was proposed as tool for solving the ODC problem using a single binary classifier. Due to its characteristics, the Data Replication Method is straightforwardly mapped into methods that optimize the decision function globally. However, the mapping process is not applicable when the methods construct the decision function locally and iteratively, like decision trees and AdaBoost (with decision stumps). In this paper we adapt the Data Replication Method for AdaBoost, by softening the constraints resulting from the data replication process. Experimental comparison with state-of-the-art AdaBoost variants in synthetic and real data show the advantages of our proposal.

Paper Citation

in Harvard Style

Costa J. and Cardoso J. (2015). oAdaBoost - An AdaBoost Variant for Ordinal Classification . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 68-76. DOI: 10.5220/0005191600680076

in Bibtex Style

@conference{icpram15,
author={João Costa and Jaime S. Cardoso},
title={oAdaBoost - An AdaBoost Variant for Ordinal Classification},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={68-76},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005191600680076},
isbn={978-989-758-076-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - oAdaBoost - An AdaBoost Variant for Ordinal Classification
SN - 978-989-758-076-5
AU - Costa J.
AU - Cardoso J.
PY - 2015
SP - 68
EP - 76
DO - 10.5220/0005191600680076