Abstract
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.
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Flach, P., Blockeel, H., Ferri, C., Hernández-Orallo, J., Struyf, J. (2003). Decision Support for Data Mining. In: Mladenić, D., Lavrač, N., Bohanec, M., Moyle, S. (eds) Data Mining and Decision Support. The Springer International Series in Engineering and Computer Science, vol 745. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0286-9_7
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DOI: https://doi.org/10.1007/978-1-4615-0286-9_7
Publisher Name: Springer, Boston, MA
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