Machine Learning, Model Selection, Hyperparameter Tuning, Learning Curve, Cross Validation.
model with lowest complexity) whose performance is not more than a standard error below the best performing model. Subsequently, we train the model with the chosen hyperparameter set on the full training set and estimate the generalization error using the test set. Lastly, we retrain the model