What are some effective model validation techniques?

What are some effective model validation techniques?

Some effective model validation techniques 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 cross-validation divides the data into k subsets, while stratified k-fold ensures each fold has the same proportion of classes.

When should I use bootstrapping for model validation?

Bootstrapping is useful when you have a small dataset, as it allows you to create multiple samples to estimate model performance.