What are hybrid validation methods in machine learning?

What are hybrid validation methods in machine learning?

Hybrid validation methods combine different validation techniques to improve model evaluation. They often integrate k-fold cross-validation with holdout methods.

Can you give me an example of how to implement this?

Sure! You can start by splitting your dataset into training and testing sets, then apply k-fold cross-validation on the training set while keeping the testing set separate.

What are the benefits of using hybrid validation?

The benefits include better generalization, reduced overfitting, and a more reliable estimate of model performance.

Are there any drawbacks to this approach?

Yes, it can be computationally expensive and may require more time to implement compared to simpler methods.