Which statement is CORRECT about cross validation in machine learning? Ink$-$fold cross validation, all k iterations use the same one fold as the testing set. $5-$fold cross validation is less likely to lead to overfitting than $20-$fold cross validation. In k$-$fold cross validation, each data point is contained in k folds. $5-$fold cross validation always provides a better fit than $10-$fold cross validation$\mathrm{.}1$