Re-validating

It is rare to put a model into production that never requires updating or re-training. A recommender system may need regular re-training as user preferences shift. An image recognition model for car makes and models may need re-training as more models come onto the market. A behavioral forecasting tool that produces one model for each device in an IoT population may need continuous monitoring to ensure that each model still satisfies the desired accuracy criterion, and to retrain those that are not.

The re-validation process is a continuous process where the accuracy of the model is tested and, if it is deemed to have decreased, an automated or manual process is triggered to re-train it, ensuring that the results are always optimal.