  This paper continues study, both theoretical and empirical, of the method of
Venn prediction, concentrating on binary prediction problems. Venn predictors
produce probability-type predictions for the labels of test objects which are
guaranteed to be well calibrated under the standard assumption that the
observations are generated independently from the same distribution. We give a
simple formalization and proof of this property. We also introduce Venn-Abers
predictors, a new class of Venn predictors based on the idea of isotonic
regression, and report promising empirical results both for Venn-Abers
predictors and for their more computationally efficient simplified version.
