ROC and Cost Graphs for General Cost Matrix Where Correct Classifications Incur Non-zero Costs
Jihyun Kim · Communications for Statistical Applications and Methods · 2004
Often the accuracy is not adequate as a performance measure of classifiers when costs are different for different prediction errors. ROC and cost graphs can be used in such case to compare and identify cost-sensitive classifiers. We extend ROC and cost graphs so that they can be used when more general cost matrix is given, where not only misclassifications but correct classifications also incur penalties.