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A Population-Based Algorithm for Learning a Majority Rule Sorting Model with Coalitional Veto

Abstract : MR-Sort (Majority Rule Sorting) is a multiple criteria sort-ing 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 heuris-tic 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.
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https://hal.archives-ouvertes.fr/hal-01474712
Contributor : Vincent Mousseau Connect in order to contact the contributor
Submitted on : Thursday, February 23, 2017 - 10:03:59 AM
Last modification on : Sunday, June 26, 2022 - 2:26:35 AM
Long-term archiving on: : Wednesday, May 24, 2017 - 12:32:33 PM

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  • HAL Id : hal-01474712, version 1

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Olivier Sobrie, Vincent Mousseau, Marc Pirlot. A Population-Based Algorithm for Learning a Majority Rule Sorting Model with Coalitional Veto. Evolutionary Multi-Criterion Optimization, Mar 2017, Münster, Germany. pp.575-589. ⟨hal-01474712⟩

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