Identify a difference between the model evaluation methods of hold-out variation and N-fold cross validation.
A) Unlike the N-fold cross validation method, the hold-out variation method requires high amounts of training time and computer processing power.
B) Unlike in the hold-out variation method, the N-fold cross validation method randomly selects one set of two-thirds of data to build the regression model.
C) Unlike the N-fold cross validation method, the hold-out variation method divides data into many smaller subsets.
D) Unlike the hold-out sample method, the N-fold cross validation method is less sensitive to variation in training and validation datasets selection.

Question

Quizplus · Accepted Answer

N-fold cross-validation method divides the dataset into N subsets and iteratively uses one subset for validation and the rest for training, reducing sensitivity to data variation. The hold-out method splits the data only once, making it more sensitive to the specific split.

Identify a Difference Between the Model Evaluation Methods of Hold-Out