Judiciously choosing just four datasets can make 46% of forecasting models appear best-in-class and 77% top-three, so dataset selection alone can distort reported performance.
A Metric Learning Reality Check
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abstract
Deep metric learning papers from the past four years have consistently claimed great advances in accuracy, often more than doubling the performance of decade-old methods. In this paper, we take a closer look at the field to see if this is actually true. We find flaws in the experimental methodology of numerous metric learning papers, and show that the actual improvements over time have been marginal at best.
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Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine
Judiciously choosing just four datasets can make 46% of forecasting models appear best-in-class and 77% top-three, so dataset selection alone can distort reported performance.