Here, we discuss the main observed trends caused by noise, bias and variance errors. Full diagnostic tools for quantifying the contributions of different error types do not yet exist. However, with the example of these trends, a dominant error type may be identifiable and treatable. We attempt to give practical advice on how to improve model performance in each of those cases.