Seasonality - recurring but not necessarily periodic data patterns - is a staple of time series modeling. Since capturing true seasonality greatly enhances model accuracy, we wanted to share our thoughts and experience on the detection and modeling of such data patterns.
In a previous post, we explained the concept of cross-validation for time series, aka backtesting, and why proper backtests matter for time series modeling.
Our goal in this post is to discuss our standard strategy (beyond respecting basic time series modeling principles) for building accurate predictive models. We will use the example of commodity purchasing optimization.
What is Facebook's Prophet? Prophet is a forecasting (i.e. time-series specific) algorithm open-sourced by Facebook in February 2017, and belonging to the GAM family of algorithms.
