Over and Underestimate Loss Metrics
For a model, metrics like MAE and RMSE and so on quantify how accurate a prediction is. However, the vast majority of metrics are symmetric, meaning they care equally about overestimates and underestimates. So far, I have found really one relatively common way for caring about direction: Mean Logarithmic Error (MLE). I also created the […]
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