Given a sequence of observable variables {(x1,y1),…,(xn,yn)}\{(x_1, y_1), \ldots, (x_n, y_n)\}{(x1,y1),…,(xn,yn)}, the conformal prediction method estimates a confidence set for yn+1y_{n+1}yn+1 given xn+1x_{n+1}xn+1 that is valid for any finite sample size by merely assuming that the joint distribution of the data is permutation invariant. Although attractive, computing such a set is computationally infeasible in most regression problems…
Conformal Prediction via Regression-as-Classification – Apple Machine Learning Research
