How do I choose the value of k in k-fold validation?

How do I choose the value of k in k-fold validation?

Choosing the value of k in k-fold validation depends on your dataset size and the trade-off between bias and variance. A common choice is 5 or 10.

What happens if I choose a very high value for k?

A high value for k means more folds, which can lead to lower bias but higher variance. It also increases computation time.

Is there a rule of thumb for selecting k?

Yes, a common rule of thumb is to set k to the square root of the number of samples in your dataset.

Can I use cross-validation with small datasets?

Absolutely! Cross-validation is particularly useful for small datasets as it helps in making the most of limited data.