Machine Learning, Model Selection, Hyperparameter Tuning, Learning Curve, Cross Validation.
fit and model simplicity, for instance the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Both penalize the number of model parameters but reward goodness of fit on the training set, hence the best model is the one with lowest AIC/BIC. BIC penalizes model