Machine Learning, Model Selection, Hyperparameter Tuning, Learning Curve, Cross Validation.
should be fairly certain that the model’s performance will not degrade when it is confronted with new data. But why do we need the distinction between model selection and model evaluation? The reason is overfitting. If we estimate the generalization error of our selected model on the same data