  We study optimal conformity measures for various criteria of efficiency of
classification in an idealised setting. This leads to an important class of
criteria of efficiency that we call probabilistic; it turns out that the most
standard criteria of efficiency used in literature on conformal prediction are
not probabilistic unless the problem of classification is binary. We consider
both unconditional and label-conditional conformal prediction.
