  Split conformal prediction is a computationally efficient method for
performing distribution-free predictive inference in regression. It involves,
however, a one-time random split of the data, and the result depends on the
particular split. To address this problem, we propose multi split conformal
prediction, a simple method based on Markov's inequality to aggregate single
split conformal prediction intervals across multiple splits.
