The reliability of analogy-based prediction

Abstract

This paper is focused on choosing a sufficient number of runs of a coupling Markov chain that makes it possible to generate, with a high confidence level, hypotheses such that at least one of them is inserted into any test example with high probability of positive prediction. The proposed technique is based on the Vapnik–Chervonenkis resampling method.