Saesonal-Forecasting-Code-Pipeline

In retail sector few NOOS(never oot of stock items) exhibit a peculiar type of seasonality and mostly it was event base , and multiplicative in nature.Machine Learning models are very diffcilut to estimate that Multiplicative pattern YoY. So this arhictecture will build on Box-Jenkinson methodology,it works as follows:

  1. Identfy the series is Stationary or Non-Stationary
  2. Tag the treatment require for make it a stationary time series
  3. Then it will find for Yearly seasonality Exist or Not
  4. Then do the simulation using auto_arima() -- both the parameters-p,d,q & P,D,Q
  5. Then it will do the forecasting