Ensemble Cross-Conformal Prediction

Abstract

The cross-conformal prediction is an approach to confidence region prediction. It provides a trade-off between the validity and informational efficiency of the prediction regions from one hand and the computational complexity from another. In this paper we introduce a new cross-conformal approach based on ensembles. The new approach is more computationally efficient and provides gains in the validity and informational efficiency of the prediction regions. Hence, it is a good candidate for big data (analytics) when prediction regions with confidence values are required.