Your question is Optimizing ML Model Performance. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You're iterating on a supervised learning model and need to improve its performance without overfitting. You want a structured way to decide whether to change features, model complexity, regularization, or training setup.
How do you optimize the performance of a machine learning model?