7 Methods of cross-validation and bootstrapping
K. Arthi, Veeramalai Sankaradass, Nikhat Parveen, J. Muralidharan · 2023
A statistical method called cross-validation is used to determine a machine learning model’s parameters and gauge its correctness. It is a type of resampling method where the dataset is arbitrarily split into training and test sets. Using different subsets of the same data, the model is tested and trained. Comparing the projected values from the testing data with the actual values of the same data allows one to evaluate the model’s performance.