Status of a Predictive Model
Once your predictive model is saved, it is added to the list of predictive models contained in your predictive scenario with the status Not Trained. From this area, you are able to monitor the status of your predictive model at each step. The predictive model list is located at the bottom of the screen.
When you train or apply your predictive model, you can get the following types of information on the training or apply process:
| Icon | Status | Means |
|---|---|---|
 |
Warning | The training/apply ended with warnings. It means that the training/apply task could be
run: You might need to check the Status panel
for more information on these warning and update your predictive
model settings. For the training, the application can display a debriefing. The status of the predictive model will be Trained with Warning. For the apply, the application could apply the predictive model. However as some warnings were found, the status is Applyed with Warning. After 10 minutes, the status will be reverted to the previous status "trained with warning" or "trained". |
 |
Error | The training/apply ended with errors. The predictive model could not be applied or
trained. You might need to check the Status
panel for more information and update your predictive model
settings. For the training, the application could not trained the predictive model and no debriefing are available. The status of the predictive model will be Train Failed. For the apply, the application could not apply the predictive model. The status of the predictive model will be Apply Failed." After 10 minutes, the status will be reverted to the previous status Train Failed or Not Trained. Note that you can look for specific messages relating to errors in the Status panel. |
 |
Trained | The training/apply ended with success. For the training, the application can display a debriefing. The status of the predictive model will be Trained. For the apply, the application could apply the predictive model. After 10 minutes, the status will be reverted to the previous status Trained. |
For Time series predictive models that are split up into entities, errors/warnings are displayed in the debriefing reports directly and exact error / warning is displayed per entity.
.