Cross Validation

Cross-validation is a technique to evaluate model performance on unseen data It involves splitting dataset into training and testing sets repeatedly This helps to prevent overfitting by providing an unbiased estimate of error The model's performance is measured on the held-out test set each time Cross-validation reduces overestimation of model's performance on training data