What are the types of cross-validation?

What are the different types of cross-validation in machine learning?

There are several types of cross-validation, including k-fold, stratified k-fold, leave-one-out, and more. Would you like details on each?

Yes, please explain k-fold cross-validation.

K-fold cross-validation involves splitting the dataset into 'k' subsets. The model is trained on 'k-1' subsets and tested on the remaining one, repeating this process 'k' times.

What about stratified k-fold?

Stratified k-fold ensures that each fold has the same proportion of classes as the entire dataset, which is especially useful for imbalanced datasets.

Can you tell me about leave-one-out cross-validation?

Leave-one-out cross-validation is a special case of k-fold where 'k' equals the number of data points. Each data point is used once as a test set while the rest serve as the training set.