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» Optimizing abstaining classifiers using ROC analysis
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ICML
2003
IEEE
14 years 6 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...
DICTA
2007
13 years 7 months ago
K-means Clustering for Classifying Unlabelled MRI Data
Texture analysis of the liver for the diagnosis of cirrhosis is usually region-of-interest (ROI) based. Integrity of the label of ROI data may be a problem due to sampling. This p...
Gobert N. Lee, Hiroshi Fujita
CORR
2000
Springer
84views Education» more  CORR 2000»
13 years 5 months ago
Robust Classification for Imprecise Environments
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building ro...
Foster J. Provost, Tom Fawcett
BIB
2011
12 years 9 months ago
Using cross-validation to evaluate predictive accuracy of survival risk classifiers based on high-dimensional data
Developments in whole genome biotechnology have stimulated statistical focus on prediction methods. We review here methodology for classifying patients into survival risk groups a...
Richard M. Simon, Jyothi Subramanian, Ming-Chung L...
ICML
2002
IEEE
14 years 6 months ago
Learning Decision Trees Using the Area Under the ROC Curve
ROC analysis is increasingly being recognised as an important tool for evaluation and comparison of classifiers when the operating characteristics (i.e. class distribution and cos...
César Ferri, José Hernández-O...