When 5-fold cross-validation (k-fold cross-validation with k = 5) is performed on 1000 data points, how many data points are used for each round of training?

Answer: B. 800

In k-fold cross-validation, the data is divided into k groups; one is used for evaluation and the remaining k − 1 for training. This is repeated k times, rotating the evaluation group, and the average of the k evaluations is taken as the model's performance. With 5 folds each group has 1000 ÷ 5 = 200 points, so each round trains on 200 × 4 = 800 points, and training is done 5 times. Every data point is used for evaluation exactly once, so performance can be estimated stably even with little data.

• A. This is the number of points used for each evaluation.
• B. Correct. Training uses 4 of the 5 groups, 200 × 4 = 800 points.
• C. Training on all the data leaves no data for evaluation.