Cross-validation is a statistical method used to estimate the skill of machine learning models by partitioning data into subsets, training the model on some subsets while validating it on others. This technique helps in assessing how the results of a statistical analysis will generalize to an independent data set, thereby preventing overfitting and improving model reliability.

Cross-Validation

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