Using the Optimize app

Evaluate a trained model against a set of constraints to solve an optimization problem; for example, optimizing an Additive Manufacturing process for target material properties based on data from previous builds.

Tip: In MI Machine Learning, the process for solving an optimization problem is as follows:
  1. Create a new Criteria Set based on a trained model.
  2. Enter constraints for all input variables. Choose between any value (Full range) or greater than/less than a value.
  3. Enter goals and target values for all output variables. Use Full range for outputs with no specific target.
  4. Send the Criteria Set and model to the engine for evaluation, and track progress with the Job Queue.
  5. View the results returned by the engine in a table, or go to the Visualize app to plot them.