Model Evaluationfocuses on assessing a model’s performance, while Model Optimisationaims to improve that performance through various techniques.
Iterative Process: Model evaluation and optimization are often iterative. After evaluating a model, insights gained can guide further optimization. Conversely, after optimizing a model, it needs to be re-evaluated to ensure improvements.
Feedback Loop: Evaluation provides feedback on the effectiveness of optimization efforts, helping refine the model further.