Overview of Retraining Models

You can retrain models to respond to data and market changes. Retraining models enables you to update out-of-date models and improve model performance. When you edit a model retrain definition, you can select multiple models to be retrained at the same time. The retrain definition for a model includes the destination version and training data source. The destination version is an existing version or new version that is associated with the selected project and stores the retrained model information.
The training data source contains new data for retraining the selected models. You can also specify a location to store the comparison reports and retrain results. When you select the models to include in the comparison report, you can use the training data source or select a different data source to compare the performance of the new models. You can also specify the report options, including the name, format, and style of the comparison report. Email notifications can also be specified as part of a model retrain definition and are sent after you execute a model retrain definition.
By default, the champion model for the selected project is selected for retrain. If the Register new trained model option was selected after you execute a model retrain definition, the new models are registered to the destination version. The comparison report is available on the Results tab of the Retrain page. The definition is executed on the SAS Application Server that is specified. The report folder is stored on the SAS Content Server.
Retrain Page Overview
Note: Only R models and those that were created with SAS Enterprise Miner, SAS/STAT, and SAS/ETS can be retrained. SAS Factory Miner models and SAS Viya models that were created with SAS Visual Data Mining and Machine Learning modeling procedures cannot be retrained in SAS Model Manager. Also note this: if a SAS model package (SPK) file was created with the Model Comparison node in SAS Enterprise Miner, the SPK file contains the score code for the best model and the training code for all of the models that were part of the model comparison. Therefore, when you are retraining the model in SAS Model Manager, be aware that the algorithm that is used for the retrained model could be different.
Last updated: June 12, 2017