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ERA ranking representability: the missing link between ordinal regression and multi-class classification

Willem Waegeman UGent and Bernard De Baets UGent (2011) Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). p.1188-1193
abstract
Can a multi-class classification model in some situations be simplified to an ordinal regression model without sacrificing performance? We try to answer this question from a theoretical point of view for one-versus-one multi-class ensembles. To that end, sufficient conditions are derived for which a one-versus-one ensemble becomes ranking representable, i.e. conditions for which the ensemble can be reduced to a ranking or ordinal regression model such that a similar performance on training data is measured. As performance measure, we use the area under the ROC curve (AUC) and its reformulation in terms of graphs. For the three-class case, this results in a new type of cycle transitivity for pairwise AUCs that can be verified by solving an integer quadratic program. Moreover, solving this integer quadratic program can be avoided, since its solution converges for an infinite data sample to a simple form, resulting in a deviation bound that becomes tighter with increasing sample size.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
graph theory, integer programming, pattern classification, quadratic programming, regression analysis
in
Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA)
pages
1188 - 1193
publisher
IEEE
place of publication
Piscataway, NJ, USA
conference name
11th International conference on Intelligent Systems Design and Applications (ISDA 2011)
conference location
Cordoba, Spain
conference start
2011-11-22
conference end
2011-11-24
Web of Science type
Conference Paper
Web of Science id
12525794
ISBN
9781457716768
DOI
10.1109/ISDA.2011.6121820
project
Bioinformatics: from nucleotids to networks (N2N)
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2037292
handle
http://hdl.handle.net/1854/LU-2037292
date created
2012-02-17 14:09:59
date last changed
2013-02-27 09:11:34
@inproceedings{2037292,
  abstract     = {Can a multi-class classification model in some situations be simplified to an ordinal regression model without sacrificing performance? We try to answer this question from a theoretical point of view for one-versus-one multi-class ensembles. To that end, sufficient conditions are derived for which a one-versus-one ensemble becomes ranking representable, i.e. conditions for which the ensemble can be reduced to a ranking or ordinal regression model such that a similar performance on training data is measured. As performance measure, we use the area under the ROC curve (AUC) and its reformulation in terms of graphs. For the three-class case, this results in a new type of cycle transitivity for pairwise AUCs that can be verified by solving an integer quadratic program. Moreover, solving this integer quadratic program can be avoided, since its solution converges for an infinite data sample to a simple form, resulting in a deviation bound that becomes tighter with increasing sample size.},
  author       = {Waegeman, Willem and De Baets, Bernard},
  booktitle    = {Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA)},
  isbn         = {9781457716768},
  keyword      = {graph theory,integer programming,pattern classification,quadratic programming,regression analysis},
  language     = {eng},
  location     = {Cordoba, Spain},
  pages        = {1188--1193},
  publisher    = {IEEE},
  title        = {ERA ranking representability: the missing link between ordinal regression and multi-class classification},
  url          = {http://dx.doi.org/10.1109/ISDA.2011.6121820},
  year         = {2011},
}

Chicago
Waegeman, Willem, and Bernard De Baets. 2011. “ERA Ranking Representability: The Missing Link Between Ordinal Regression and Multi-class Classification.” In Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA), 1188–1193. Piscataway, NJ, USA: IEEE.
APA
Waegeman, W., & De Baets, B. (2011). ERA ranking representability: the missing link between ordinal regression and multi-class classification. Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA) (pp. 1188–1193). Presented at the 11th International conference on Intelligent Systems Design and Applications (ISDA 2011), Piscataway, NJ, USA: IEEE.
Vancouver
1.
Waegeman W, De Baets B. ERA ranking representability: the missing link between ordinal regression and multi-class classification. Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). Piscataway, NJ, USA: IEEE; 2011. p. 1188–93.
MLA
Waegeman, Willem, and Bernard De Baets. “ERA Ranking Representability: The Missing Link Between Ordinal Regression and Multi-class Classification.” Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). Piscataway, NJ, USA: IEEE, 2011. 1188–1193. Print.