Cross Validation: Difference between revisions

Created page with "= Cross-Validation = '''Cross-Validation''' is a statistical method used to estimate the performance of machine learning models on unseen data. It helps ensure that the model generalizes well and reduces the risk of overfitting. == Why Cross-Validation? == When training a model, it is important to test how well it performs on data it has never seen before. Simply evaluating a model on the same data it was trained on can lead to overly optimistic results. Cross-validat..."
 
 
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cross validation, k fold cross validation, stratified cross validation, model validation techniques, overfitting prevention, estimating model performance, machine learning model evaluation
cross validation, k fold cross validation, stratified cross validation, model validation techniques, overfitting prevention, estimating model performance, machine learning model evaluation
[[Category:Artificial Intelligence]]