MR-Sort (Majority Rule Sorting) is a multiple criteria sorting method which assigns an alternative a to category Ch when a is better than the lower limit of Ch on a weighted majority of criteria, and this is not true with the upper limit of Ch. We enrich the descriptive ability of MR-Sort by the addition of coalitional vetoes which operate in a symmetric way as compared to the MR-Sort rule w.r.t. to category limits, using specific veto profiles and veto weights. We describe a heuristic algorithm to learn such an MR-Sort model enriched with coalitional veto from a set of assignment examples, and show how it performs on real datasets.
CITATION STYLE
Sobrie, O., Mousseau, V., & Pirlot, M. (2017). A population-based algorithm for learning a majority rule sorting model with coalitional veto. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10173 LNCS, pp. 575–589). Springer Verlag. https://doi.org/10.1007/978-3-319-54157-0_39
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