The choice of the solution method in the construction of the forecast model

Today, let’s talk about choosing a solution method when building a forecast model. Consider the advantages and disadvantages of different methods.

1. Models of forecasting time series of the SARIMA family (AR, MA, ARIMA, SARIMA)

Advantage: A widely used method for predicting time series

Disadvantage: Slow learning curve, requires large computational resources, inability to take into account the influence of external factors.

2. Linear regression

Advantage: Fast learning curve

Disadvantage: The accuracy of the forecast, the inability to specify categories

3. Random Forest Regression

Advantage: Ability to add external factors and categories, built-in methods for assessing the significance of individual characteristics, scalability

Disadvantage: Slower in learning than linear regression; increased memory requirement.