What is the role of loss functions in model optimization?

Loss functions quantify prediction error and guide parameter updates.

Loss functions define the objective that optimization algorithms minimize. Different models use different losses: MSE for regression, log-loss for classification, hinge loss for SVM. Optimization algorithms adjust parameters to minimize this function.