DataScratch supports a total of three validators. These are used to validate that your model is accurate, and accommodate for over fitting.
Lessons on this topic
| Validator Name | Summary | Link to sklearn-documentation |
|---|---|---|
| KFold | Splits the dataset into consecutive folds. Each fold is used once as a validation set while the remaining folds form the training set. | Documentation |
| StratifiedKFold | A variation of KFold that ensures each fold has the same proportion of class labels as the entire dataset. Essential for imbalanced classification tasks. | Documentation |
| LeaveOneOut | Each learning set is created by taking all the samples except one, the remaining sample being the test set. For samples, we have different training sets. | Documentation |