Question

Is K-fold cross-validation linear in K, quadratic in K, cubic in K or exponential in K?

Answer 1

K-fold cross-validation is

(A) linear in K

(B) quadratic in K

(C) cubic in K

(D) exponential in K

Answer:

K-fold cross-validation is  linear in K.

(A) linear in K

Explanation:

Cross-validation is a powerful preventive measure against overfitting. In this method, the dataset is randomly divided into groups of K or approximately equal-sized folds. In standard k-fold cross-validation, we divide the data into k subsets, which are called folds.

In this process, there is only one parameter k, which represents the number of groups in which a given data sample should be divided into a group of holdout or test data sets. Increasing K may improve your accuracy measure (yes, think at the beginning), but it does not improve the basic accuracy you are trying to measure.

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