What is validation in machine learning?

What is validation in machine learning?

Validation in machine learning is the process of evaluating a model's performance on a separate dataset to ensure it generalizes well.

Why is validation important?

Validation is crucial because it helps prevent overfitting, ensuring that the model performs well on unseen data.

What are the different types of validation techniques?

Common validation techniques include k-fold cross-validation, holdout validation, and stratified sampling.

How do I choose the right validation technique for my model?

Choosing the right technique depends on your dataset size, model complexity, and the specific problem you're addressing.