Hi @Juan
Yes, the Classification Learner app in MATLAB uses stratified k-fold cross-validation by default when performing classification tasks.
Here’s how it works:
- When you select cross-validation in the app, it internally uses the "cvpartition" function with the response variable (class labels) as the grouping variable.
- In "cvpartition" when a grouping variable is provided, stratification is automatically applied. This ensures that each fold maintains the same class distribution as the original dataset.
- Even in the generated code (e.g., crossval(trainedClassifier.ClassificationEnsemble, 'KFold', 5)), the crossval function uses the model’s response variable behind the scenes, which results in stratified partitioning.
This behavior is specific to classification problems. For regression tasks, stratification is not applied because there are no discrete class labels to stratify by.
For more details, please refer to the MathWorks documentation:
Hope this helps!
