Model maintenance

Get feedback from real-world interactions and redefine the goals for the next iteration of deployment.

Eliminate unnecessary features. Regularly evaluate the effect of removing individual features from a given model, because unimportant features add noise to your feature space. A model's feature space should only contain relevant and important features for the given task.

Over time, as the input data distribution changes, the model's performance may weaken. Schedule a periodical model retraining, so that it has always learned from the most recent data to prevent model staleness. Set the schedule based on your data variations; a period after which you would expect different insights from the model.

Set an automatic scheduled model retraining in ION Workflows. See Updating the model on a schedule