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ML
2006
ACM
109views Machine Learning» more  ML 2006»
13 years 4 months ago
Cost curves: An improved method for visualizing classifier performance
Abstract This paper introduces cost curves, a graphical technique for visualizing the performance (error rate or expected cost) of 2-class classifiers over the full range of possib...
Chris Drummond, Robert C. Holte
ICML
2003
IEEE
14 years 5 months ago
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...
ROCAI
2004
Springer
13 years 10 months ago
What ROC Curves Can't Do (and Cost Curves Can)
Abstract. This paper shows that ROC curves, as a method of visualizing classifier performance, are inadequate for the needs of Artificial Intelligence researchers in several sign...
Chris Drummond, Robert C. Holte
BMVC
1998
13 years 6 months ago
Realisable Classifiers: Improving Operating Performance on Variable Cost Problems
A novel method is described for obtaining superior classification performance over a variable range of classification costs. By analysis of a set of existing classifiers using a r...
Martin J. J. Scott, Mahesan Niranjan, Richard W. P...
ISSRE
2008
IEEE
13 years 11 months ago
Cost Curve Evaluation of Fault Prediction Models
Prediction of fault prone software components is one of the most researched problems in software engineering. Many statistical techniques have been proposed but there is no consen...
Yue Jiang, Bojan Cukic, Tim Menzies