Tutorial by Examples

Learning the parameters of a prediction function and testing it on the same data is a methodological mistake: a model that would just repeat the labels of the samples that it has just seen would have a perfect score but would fail to predict anything useful on yet-unseen data. This situation is call...

K-fold cross-validation is a systematic process for repeating the train/test split procedure multiple times, in order to reduce the variance associated with a single trial of train/test split. You essentially split the entire dataset into K equal size "folds", and each fold is used once fo...