In this chapter we give an introduction to ROC (``receiver operating characteristics'') analysis and its applications to data mining. We argue that ROC analysis provides decision support for data mining in several ways. For model selection, ROC analysis establishes a method to determine the optimal model once the operating characteristics for the model deployment context are known. We also show how ROC analysis can aid in constructing and refining models in the modeling stage.
|Translated title of the contribution||Decision support for data mining: introduction to ROC analysis and its application|
|Title of host publication||Data Mining and Decision Support: Aspects of Integration and Collaboration|
|Publisher||Kluwer Academic Publishers|
|Publication status||Published - 2003|
Bibliographical noteOther page information: 81-90
Other identifier: 1000701