Learning the Parameters of a Multiple Criteria Sorting Method
From MaRDI portal
Publication:3095305
DOI10.1007/978-3-642-24873-3_17zbMath1233.90247OpenAlexW102689899MaRDI QIDQ3095305
Agnès Leroy, Marc Pirlot, Vincent Mousseau
Publication date: 28 October 2011
Published in: Algorithmic Decision Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-642-24873-3_17
Searching and sorting (68P10) Multi-objective and goal programming (90C29) Learning and adaptive systems in artificial intelligence (68T05)
Related Items (23)
An interactive algorithm for multiple criteria constrained sorting problem ⋮ Integrating large positive and negative performance differences into multicriteria majority-rule sorting models ⋮ An efficient SAT formulation for learning multiple criteria non-compensatory sorting rules from examples ⋮ Learning criteria weights of an optimistic Electre Tri sorting rule ⋮ Inferring a hierarchical majority-rule sorting model ⋮ Learning monotone preferences using a majority rule sorting model ⋮ A MIP-based approach to learn MR-sort models with single-peaked preferences ⋮ A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes ⋮ Interactive portfolio selection involving multicriteria sorting models ⋮ Dynamic-R: a ``challenge-free method for rating problem statements ⋮ A theoretical look at \textsc{Electre Tri}-nB and related sorting models ⋮ Multiple criteria sorting models and methods. I: Survey of the literature ⋮ A decomposition based minimax regret approach for inverse multiple criteria sorting problem ⋮ A consolidated approach to the axiomatization of outranking relations: a survey and new results ⋮ Handling imprecise and missing evaluations in multi-criteria majority-rule sorting ⋮ Enumerating and categorizing positive Boolean functions separable by a \(k\)-additive capacity ⋮ On the relations between ELECTRE TRI-B and ELECTRE TRI-C and on a new variant of ELECTRE TRI-B ⋮ Interactive elicitation of a majority rule sorting model with maximum margin optimization ⋮ Learning non-compensatory sorting models using efficient SAT/MaxSAT formulations ⋮ Deep preference learning for multiple criteria decision analysis ⋮ Integrating preferences within multiobjective flexible job shop scheduling ⋮ A generalized approach to ordinal classification based on the comparison of actions with either limiting or characteristic profiles ⋮ Ranking with multiple reference points: efficient SAT-based learning procedures
Uses Software
This page was built for publication: Learning the Parameters of a Multiple Criteria Sorting Method
