The use of the area under the ROC curve in the evaluation of machine learning algorithms

scholarly article by Andrew P. Bradley published July 1997 in Pattern Recognition

The use of the area under the ROC curve in the evaluation of machine learning algorithms is …
instance of (P31):
scholarly articleQ13442814

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P8978DBLP publication IDjournals/pr/Bradley97
P356DOI10.1016/S0031-3203(96)00142-2
P5875ResearchGate publication ID222503383

P2093author name stringAndrew P. Bradley
P2860cites workThe meaning and use of the area under a receiver operating characteristic (ROC) curveQ29547182
Models of incremental concept formationQ29998852
A method of comparing the areas under receiver operating characteristic curves derived from the same casesQ34272510
International application of a new probability algorithm for the diagnosis of coronary artery disease.Q45953387
ROC Analysis Applied to the Evaluation of Medical Imaging TechniquesQ52776850
Bootstrap Methods: Another Look at the JackknifeQ55950786
ROC curves for classification treesQ72054088
Relationship of platelet aggregation to bleeding after cardiopulmonary bypassQ72383272
P433issue7
P921main subjectmachine learningQ2539
algorithmQ8366
P304page(s)1145-1159
P577publication date1997-07-01
P1433published inPattern RecognitionQ15752055
P1476titleThe use of the area under the ROC curve in the evaluation of machine learning algorithms
P478volume30

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