Validation Data

Fundamentals

Data used for model tuning (e.g., hyperparameters).

Validation data are used to select models and hyperparameters without touching the final test set.

Purpose: Estimate generalization during development.
Best practices: Keep separate from training/test data, ensure same distribution, use meaningful metrics.
Risk: Overfitting to validation data through repeated tuning.