### 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: