July 2016
Beginner to intermediate
462 pages
9h 14m
English
Content preview from Python Data Analysis Cookbook
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Determining MAPE and MPE
The Mean Percentage Error (MPE) and Mean Absolute Percentage Error (MAPE) express forecasting errors as ratios, and they are, therefore, dimensionless and easy to interpret. As you can see in the following equations, the disadvantage of MPE and MAPE is that we run the risk of dividing by zero:
It is perfectly valid for the target variable to be equal to zero. For temperature, this happens to be the freezing point. Freezing often occurs in winter, so we either have to ignore those observations or add a constant large enough to avoid dividing by zero values. In the following section, it becomes clear that simply ignoring observations ...
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