Apply the time series model
Once you have assessed the performance of your time series model and you want to apply it, you simply save the predictive forecasts into a dataset in three simple steps.
- From your model, select Save Forecast as highlighted below.
- In the Save Forecasts dialog, provide a name for your forecast.
- Select Save.
Find your generated dataset
To find your generated dataset with the forecasts, you can either:
- From the side navigation, select Datasets then Recent Files.
- From the side navigation bar, select My Files.
Status
In the predictive model list, the status of your predictive model is updated to Applied.
Application output columns
The following columns are generated in the output dataset when a time series model is applied:
| Name | Description |
|---|---|
| Forecast | This is the column where you find the forecast values for the target based on the number of requested forecasts specified in the predictive model settings. |
| Error Min | For each requested forecast at a given horizon H, the predictive model calculates a confidence interval. The Error Min value is the lower bound of this confidence interval. It is equal to the forecasted value – sigma(RMSE)*1.96, where sigma (RMSE) represents the standard deviation of RMSE between the actual and forecasted target value at horizon H. The weighted value of 1.96 corresponds to a confidence level of 95%. |
| Error Max | For each requested forecast at a given horizon H, the predictive model calculates a confidence interval. The Error Max value is the upper bound of this confidence interval. It is equal to the forecasted value + sigma(RMSE)*1.96, where sigma(RMSE) represents the standard deviation of RMSE between the actual and forecasted target value at horizon H. The weighted value of 1.96 corresponds to a confidence level of 95%. |
You can see an example of the newly added columns in the example below:
