Machine Learning & Training

What Is Cross-Validation?

Cross-validation is a technique for assessing how well a model generalizes by repeatedly splitting the data into training and testing portions. The model is trained and evaluated on different subsets, and the results are averaged for a more reliable performance estimate. It helps reduce the chance that results depend on a single lucky or unlucky split.