The purpose of cross-validation is to
A) validate the test for different criteria.
B) try out the test with the same sample after a period of time.
C) confirm the correlation in a different sample.

Question

Quizplus · Accepted Answer

Cross-validation is a technique used to confirm that a statistical model is robust and not overfitting the data. It involves splitting the dataset into multiple subsets and training the model on one subset while testing it on the other subsets. This helps to ensure that the model can generalize well to unseen data and is not just memorizing the training data. Therefore, choice C, confirming the correlation in a different sample, best describes the purpose of cross-validation.

The Purpose of Cross-Validation Is to