The Characterization of Classification Problems by Classifier Disagreements

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.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: David M. J. Tax, Elzbieta Pekalska, Robert P. W. Duin
• Keywords: Classification Problems, Computer Vision, Disagreement Patterns, ICPR 2004, Training Set Size