The rankability of weighted data from pairwise comparisons

In prior work [4], Anderson et al. introduced a new problem, the rankability problem, which refers to dataset's inherent ability produce meaningful ranking of its items. Ranking is fundamental data science task with numerous applications that include web search, mining, cybersecurity, machine learning, and statistical learning theory. Yet little attention has been paid question whether dataset suitable for ranking. As result, when method applied low rankability, resulting may not be reliable. style='text-indent:20px;'>Rankability paper rid="b4">4] methods studied unweighted dominance relations are binary, i.e., an item either dominates or dominated by another item. In this paper, we extend rankability weighted data dominate any finite amount. We present combinatorial approaches weighted measure apply our several datasets.