Area+under+the+curve

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AUC = the **A**rea **U**nder the ROC **C**urve.

Weka uses the [|Mann Whitney statistic] to calculate the AUC ([|source]) via the [|weka.classifiers.evaluation.ThresholdCurve] class.

= Version = >= 3.5.1

= Explorer = See ROC curves.

= KnowledgeFlow = See ROC curves.

= Commandline = Classifiers can output the AUC if the //-i// option is provided. The //-i// option provides detailed information per class.

Running the J48 classifier on the iris UCI dataset with the following commandline: code format="bash" java [CLASSPATH|-classpath ] weka.classifiers.trees.J48 -t /some/where/iris.arff -i code produces this output: code format="text" == Detailed Accuracy By Class == TP Rate  FP Rate   Precision   Recall  F-Measure   ROC Area  Class 0.98     0          1         0.98      0.99       0.99     Iris-setosa 0.94     0.03       0.94      0.94      0.94       0.952    Iris-versicolor 0.96     0.03       0.941     0.96      0.95       0.961    Iris-virginica code

= See also =
 * ROC curves
 * [|Mann Whitney statistic] on WikiPedia

= Links =
 * [|University of Nebraska Medical Center, Interpreting Diagnostic Tests]
 * [|weka.classifiers.evaluation.ThresholdCurve] Javadoc