Can k-fold cross-validation help to improve your prediction for live data that is characterized by the same patterns of association as your original data? Why or why not?
A) Yes, because k-fold cross-validation ensures that the model is robust and generalizes well to unseen data.
B) No, because k-fold cross-validation can only be applied to training data, not live data.
C) Yes, because k-fold cross-validation allows for the assessment of model performance on multiple subsets of the data, reducing the risk of overfitting.
D) No, because k-fold cross-validation does not consider the characteristics of live data and may not accurately reflect its patterns of association.