Which statement is true about cross-validation.
A)It can be used for evaluating the model for chance variations in the data and other problems associated with regression.
B)It examines whether the regression model continues to hold on comparable data not used in the estimation.
C)A special form of validation is called double cross-validation where the sample is split into halves.
D)All of the above statements are true.

Question

Quizplus · Accepted Answer

All of the given statements about cross-validation are true. Cross-validation is a technique used to evaluate machine learning models by using different subsets of the data for training and testing. It helps in evaluating the model's performance on unseen data and also helps in detecting overfitting or underfitting problems. "Double cross-validation" refers to a technique where the sample is split into halves, and the validation process is repeated twice, each time using a different half for validation and training.

Which Statement Is True About Cross-Validation