AI engineering glossary · Time series recsys
What is WAPE (weighted absolute percentage error)?
Weighted absolute percentage error (also called WAPE): The sum of absolute errors divided by the sum of actuals, giving a single percentage weighted by volume. It is widely used in retail because large items count more, and it does not explode for small ones.
Weighted absolute percentage error: an example
Errors of 10, 5 and 20 units on actual sales of 100, 50 and 200 units give WAPE = 35/350 = 10 percent.
Related terms
More Time series recsys terms
- White noise
- Wide and Deep
- Additive decomposition
- Alternating least squares
- Anomaly detection (time series)
- ARCH model
- ARIMA
- ARIMAX
Where you learn it
Weighted absolute percentage error is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.