Investigating the error measures

It’s not enough to just know the different metrics; we also need to understand how these work, what are they good for, and what are they not good for. We can start with the basic errors and work our way up because understanding the properties of basic errors such as absolute error, squared error, percent error, and symmetric error will help us understand the others as well, as most of the other metrics are derivatives of these primary errors, either aggregating them or using relative benchmarks.

Let’s do this investigation using a few experiments and understand them through the results.

Notebook alert:

The notebook for running these experiments on your own is 01-Loss_Curves_and_Symmetry.ipynb in the Chapter19 folder.

Loss curves and complementarity

All these base errors depend on two factors—forecasts and actual observations. We can examine the behavior of these metrics if we fix one and alter...