Source
Towards Data Science
Towards Data Science
Source
Towards Data Science
Towards Data Science
- Oct 21, 2021
- 7 minutes
In yesterday’s article, Heiko discussed the Darts multi-method package and how to run a forecast tournament on a given time series. He reviewed which of the five chosen models — exponential smoothing, Theta, SARIMA, naïve forecast, and facebook Prophet — would generate a better fit to the source data, the classic airline passenger numbers of Box & Jenkins. Darts’ Swiss Knife for Time Series Forecasting | Oct, 2021 | Towards Data Science
If you read the article, you may remember that the grid of forecast plots had left the sixth cell, in the bottom-right corner, conspicuously empty.
Empty cell
Let’s fill this gap by going one step further than yesterday:
We will create an ensemble forecast that combines the five methods, with no more than a single line of code.
Will the ensemble scenario show forecast qualities that none of the individual methods can provide?
