K-Fold Cross-Validation Size Calculator

Summary

Enter your dataset size and number of folds to see exact training and validation sample counts for each fold.

How it works

1. Enter the total number of samples in your dataset.
2. Set k — the number of folds you want to split the data into.
3. The calculator divides the dataset into k roughly equal folds.
4. Remainder samples (when dataset size is not divisible by k) are distributed one per fold across the first folds.
5. Each row shows which fold acts as the validation set while the rest form the training set.
6. Use the results to allocate data in your cross-validation loop.

Use cases

• Verify fold sizes before writing a cross-validation training loop.
• Plan compute time by knowing exact training set sizes per fold.
• Check how remainder samples are distributed when dataset size is not divisible by k.
• Compare the effect of different k values on validation set size.
• Communicate dataset splits clearly in research papers or team discussions.
• Quickly estimate validation set size for a given dataset and fold count.

Frequently Asked Questions