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.
翻译:分解一致预测是一种计算效率高的方法,用来计算回归中无分配预测的推论。 但是,它涉及一次性随机数据分割,结果取决于特定分割。 为了解决这个问题,我们建议多分分配一致预测,这是一种基于Markov不平等的简单方法,可以将多个分割的单一分割一致预测间隔加在一起。