What are some common methods for validating machine learning models?

What are some common methods for validating machine learning models?

Common methods include cross-validation, holdout validation, and bootstrapping.

Can you explain cross-validation in more detail?

Sure! Cross-validation involves partitioning the data into subsets, training the model on some subsets and validating it on others.

What is the difference between k-fold and stratified k-fold cross-validation?

K-fold divides the data into k subsets, while stratified k-fold ensures each fold has the same proportion of classes as the entire dataset.

When should I use holdout validation instead of cross-validation?

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