Relative cost curves: An alternative to AUC and an extension to 3-class problems

Montvida, Olga, and Klawonn, Frank. "Relative cost curves: An alternative to AUC and an extension to 3-class problems." Kybernetika 50.5 (2014): 647-660. <http://eudml.org/doc/262159>.

@article{Montvida2014,
abstract = {Performance evaluation of classifiers is a crucial step for selecting the best classifier or the best set of parameters for a classifier. Receiver Operating Characteristic (ROC) curves and Area Under the ROC Curve (AUC) are widely used to analyse performance of a classifier. However, the approach does not take into account that misclassification for different classes might have more or less serious consequences. On the other hand, it is often difficult to specify exactly the consequences or costs of misclassifications. This paper is devoted to Relative Cost Curves (RCC) - a graphical technique for visualising the performance of binary classifiers over the full range of possible relative misclassification costs. This curve provides helpful information to choose the best set of classifiers or to estimate misclassification costs if those are not known precisely. In this paper, the concept of Area Above the RCC (AAC) is introduced, a scalar measure of classifier performance under unequal misclassification costs problem. We also extend RCC to multicategory problems when misclassification costs depend only on the true class.},
author = {Montvida, Olga, Klawonn, Frank},
journal = {Kybernetika},
keywords = {classifier; performance evaluation; misclassification costs; cost curves; ROC curves; AUC; classifier; performance evaluation; misclassification costs; cost curves; receiver operating characteristic (ROC) curves; area under the ROC curve (AUC)},
language = {eng},
number = {5},
pages = {647-660},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Relative cost curves: An alternative to AUC and an extension to 3-class problems},
url = {http://eudml.org/doc/262159},
volume = {50},
year = {2014},
}

TY - JOUR
AU - Montvida, Olga
AU - Klawonn, Frank
TI - Relative cost curves: An alternative to AUC and an extension to 3-class problems
JO - Kybernetika
PY - 2014
PB - Institute of Information Theory and Automation AS CR
VL - 50
IS - 5
SP - 647
EP - 660
AB - Performance evaluation of classifiers is a crucial step for selecting the best classifier or the best set of parameters for a classifier. Receiver Operating Characteristic (ROC) curves and Area Under the ROC Curve (AUC) are widely used to analyse performance of a classifier. However, the approach does not take into account that misclassification for different classes might have more or less serious consequences. On the other hand, it is often difficult to specify exactly the consequences or costs of misclassifications. This paper is devoted to Relative Cost Curves (RCC) - a graphical technique for visualising the performance of binary classifiers over the full range of possible relative misclassification costs. This curve provides helpful information to choose the best set of classifiers or to estimate misclassification costs if those are not known precisely. In this paper, the concept of Area Above the RCC (AAC) is introduced, a scalar measure of classifier performance under unequal misclassification costs problem. We also extend RCC to multicategory problems when misclassification costs depend only on the true class.
LA - eng
KW - classifier; performance evaluation; misclassification costs; cost curves; ROC curves; AUC; classifier; performance evaluation; misclassification costs; cost curves; receiver operating characteristic (ROC) curves; area under the ROC curve (AUC)
UR - http://eudml.org/doc/262159
ER -