1. A method of deciding whether a data set is acceptable for making a decision, the data set being comprised of information pieces about objects, each object having a number of modalities, the number being at least two, comprising: provide a first probability partition array (“Pm(i,j)”), the Pm(i,j) being comprised of probability values for information pieces in the data set, each probability value in the Pm(i,j) corresponding to the probability of an authentic match; provide a second probability partition array (“Pfm(i,j)”), the Pfm(i,j) being comprised of probability values for information pieces in the data set, each probability value in the Pfm(i,j) corresponding to the probability of a false match; identify a first index set (“A”), the indices in set A being the (i,j) indices that have values in both Pfm(i,j) and Pm(i,j); identify a second index set (“Z∞”), the indices of Z∞ being the (i,j) indices in set A where both Pfm(i,j) is larger than zero and Pm(i,j) is equal to zero; determine FAR Z∞ , where FAR Z ∞ =1−Σ (i,j)εZ ∞ P fm (i, j); compare FAR Z∞ to a desired false-acceptance-rate (“FAR”); if FAR Z∞ is greater than the desired false-acceptance-rate, then reject the data set.