Evaluating Discrete Choice Prediction Models When the Evaluation Data is Corrupted: Analytic Results and Bias Corrections for the Area Under the ROC
Data Min. Knowl. Discov., Volume 30, Issue 4, 2015.
ROCModel validationPredictionData corruptionBias correctionMore(5+)
There has been a growing recognition that issues of data quality, which are routine in practice, can materially affect the assessment of learned model performance. In this paper, we develop some analytic results that are useful in sizing the biases associated with tests of discriminatory model power when these are performed using corrupt ...More
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