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Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
HPL-2009-359 Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement - Forman, George; Scholz, Martin
Keyword(s): AUC, F-measure, machine learning, ten-fold cross-validation, classification performance measurement, high class imbalance, class skew, experiment protocol Abstract: Cross-validation is a mainstay for measuring performance and progress in machine learning. There are subtle differences in how exactly to compute accuracy, F-measure and Area Under the ROC Curve (AUC) in cross-validation studies. However, these details are not discussed in the literature, and incomp ... Full Report More... |
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