Cost-sensitive classifier evaluation using cost curves

Authors:
Robert C. Holte;Chris Drummond
Affiliations:
Computing Science Department, University of Alberta, Edmonton, Alberta, Canada;Institute for Information Technology, National Research Council, Ontario, Canada
Venue:
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2008

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Abstract

The evaluation of classifier performance in a cost-sensitive setting is straightforward if the operating conditions (misclassification costs and class distributions) are fixed and known. When this is not the case, evaluation requires a method of visualizing classifier performance across the full range of possible operating conditions. This talk outlines the most important requirements for cost-sensitive classifier evaluation for machine learning and KDD researchers and practitioners, and introduces a recently developed technique for classifier performance visualization - the cost curve - that meets all these requirements.