Which of the following best describes k$-$fold cross$-$validation?

a$.$ A procedure of doing regression

b$.$ A method to divide the data into k equal$-$sized, mutually exclusive, and collectively exhaustive subsets

c$.$ A post$-$processing step to add a desired number of observations to compose the test set

d$.$ A procedure to optimize a model