Generalization of leave-one-out cross-validation formula for linear statistical models

Savaş Dayanık

Industrial Engineering Department

Bilkent University

Invited by: Bülent Karasözen

Place: IAM S212

Date/Time: 23.05.2017 -15.40

Abstract: In comparing alternative linear models, one is interested in the mean squared error of each model on unseen data. This is often measured with cross-validation. However, as the number of folds increases, the computations can get prohibitively intense. It is well known that leave-one-out crossvalidation can be calculated by fitting each model to the entire data set only once. In this talk, we will show that the same is possible for any arbitrary k-fold crossvalidation.

Event Date: 
23. May 2017 - 15:40 - 16:40