On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions

dc.contributor.author	Webb Geoffrey I
dc.contributor.author	Ting Kai Ming
dc.date.accessioned	2017-11-14T17:01:33Z
dc.date.available	2017-11-14T17:01:33Z
dc.date.issued	2004
dc.identifier.uri	http://hdl.handle.net/123456789/3753
dc.description.abstract	We counsel caution in the application of ROC analysis for prediction of classifier performance under varying class distributions. We argue that it is not reasonable to expect ROC analysis to provide accurate prediction of model performance under varying distributions if the classes contain causally relevant subclasses whose frequencies may vary at different rates or if there are attributes upon which the classes are causally dependent.
dc.format	application/pdf
dc.title	On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions
dc.type	journal-article
dc.source.volume	58
dc.source.journal	Machine Learning