We introduce the jackknife+, a novel method for constructing predictive confidence intervals that is robust to the distribution of the data. The jackknife+ modifies the well-known jackknife (leave-one-out cross-validation) to account for the variability in the fitted regression function when we subsample the training data. Assuming exchangeable ...
Creator:
Barber, Rina (University of Chicago)
Created:
2019-06-18
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.