Data Splitting

+**Data Splitting**

+Data splitting is the practice of dividing a dataset into distinct subsets to evaluate the performance of a [Machine Learning](/wiki/machine_learning) model. This partitioning typically creates a [Training Data](/wiki/training_data) set for model learning and separate sets for validation and testing, ensuring an unbiased assessment of the model's generalization capabilities.

+## See also

+- [Cross-validation](/wiki/cross-validation)

+- [Overfitting](/wiki/overfitting)