The paper repackages signal-to-noise ratio as a data-quality metric, DDR, and uses controlled synthetic noise to draw accuracy-DDR curves and define a trustworthiness portfolio.
Performance evaluation in machine learning: the good, the bad, the ugly, and the way forward
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Towards Modeling Data Quality and Machine Learning Model Performance
The paper repackages signal-to-noise ratio as a data-quality metric, DDR, and uses controlled synthetic noise to draw accuracy-DDR curves and define a trustworthiness portfolio.