What is the difference between k-fold and holdout validation?

What is the difference between k-fold and holdout validation?

K-fold validation divides the dataset into k subsets, while holdout uses a single train-test split.

Which method is better for model evaluation?

K-fold is generally better as it uses more data for training and testing, reducing variance.

Can you explain how k-fold validation works?

Sure! In k-fold, the data is split into k parts. The model is trained on k-1 parts and tested on the remaining part, repeating this k times.

What are the advantages of using holdout validation?

Holdout is simpler and faster, making it suitable for large datasets where k-fold might be computationally expensive.