AI engineering glossary · Time series recsys
What is hierarchical forecasting?
Hierarchical forecasting: Forecasting a collection of series that add up in a structure, such as store to city to state, so forecasts at different levels can be produced and must agree. Separately made forecasts often do not sum correctly.
Hierarchical forecasting: an example
Forecast demand for each of 500 stores, each city and the whole country.
Related terms
More Time series recsys terms
- Holiday effect
- Holt's linear method
- Holt-Winters method
- Hybrid recommender
- Intermittent demand
- Inverse propensity scoring
- Item-based collaborative filtering
- Kalman filter
Where you learn it
Hierarchical forecasting is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.