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AUSAI
2006
Springer

Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation

9 years 9 months ago
Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation
Different evaluation measures assess different characteristics of machine learning algorithms. The empirical evaluation of algorithms and classifiers is a matter of on-going debate between researchers. Although most measures in use today focus on a classifier's ability to identify classes correctly, we suggest that, in certain cases, other properties, such as failure avoidance or class discrimination may also be useful. We suggest the application of measures which evaluate such properties. These measures
Marina Sokolova, Nathalie Japkowicz, Stan Szpakowi
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where AUSAI
Authors Marina Sokolova, Nathalie Japkowicz, Stan Szpakowicz
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