Machine Learning, Model Selection, Hyperparameter Tuning, Learning Curve, Cross Validation.
matryoshka: nested cross-validation for algorithm selection For algorithm selection we need a more elaborate method. Here, nested cross-validation comes to the rescue, which is illustrated in Fig. 3 and works as follows: We split the data into K smaller sets (outer fold). Each of the K folds we set