The Characterization of Classification Problems by Classifier Disagreements

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17th International Conference on Pattern Recognition (ICPR'04) - Volume 1

Cambridge UK

August 23-August 26

ISBN: 0-7695-2128-2

	ASCII Text	x
	Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax, "The Characterization of Classification Problems by Classifier Disagreements," Pattern Recognition, International Conference on, vol. 1, pp. 140-143, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004.

	BibTex	x
	@article{ 10.1109/ICPR.2004.1334027, author = {Robert P. W. Duin and Elzbieta Pekalska and David M. J. Tax}, title = {The Characterization of Classification Problems by Classifier Disagreements}, journal ={Pattern Recognition, International Conference on}, volume = {1}, year = {2004}, issn = {1051-4651}, pages = {140-143}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334027}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - The Characterization of Classification Problems by Classifier Disagreements SN - 1051-4651 SP140 EP143 A1 - Robert P. W. Duin, A1 - Elzbieta Pekalska, A1 - David M. J. Tax, PY - 2004 KW - null VL - 1 JA - Pattern Recognition, International Conference on ER -

Robert P. W. Duin, Delft University of Technology, The Netherlands

Elzbieta Pekalska, Delft University of Technology, The Netherlands

David M. J. Tax, Delft University of Technology, The Netherlands

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334027

In this paper we try to characterize a set of classification problems. For this, we use the disagreement between a set of standard classifiers. The disagreement patterns do not only point towards different types of classification problems, but also indicate the novelty and the usefulness of a classifier with respect to a set of classification problems and classifiers. Some experiments show when known classification problems become unknown after changing their feature size or their training set size.

Citation:

Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax, "The Characterization of Classification Problems by Classifier Disagreements," icpr, vol. 1, pp.140-143, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004

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