+**Cross-validation** is a statistical method to assess how a [Machine Learning](/wiki/Machine_Learning) model generalizes to an independent dataset. It partitions data into subsets, training on some and validating on others, offering a robust measure of performance and helping to prevent [Overfitting](/wiki/Overfitting). This process reveals how well a model will perform on unseen data.
+## See also
+- [Validation Set](/wiki/Validation_Set)
+- [Training Data](/wiki/Training_Data)
+- [Model Evaluation](/wiki/Model_Evaluation)