Given a ranking of actions evaluated by a set of evaluation criteria, we are constructing a rough approximation of the preference relation known from this ranking. The rough approximation of the preference relation is a starting point for mining "if..., then..." decision rules constituting a symbolic preference model. The set of rules is induced such as to be compatible with a concordance discordance preference model used in well-known multicriteria decision aiding methods. Application of the set of decision rules to a new set of actions gives a fuzzy outranking graph. Positive and negative flows are calculated for each action in the graph, giving arguments about its strength and weakness. Aggregation of both arguments leads to a final ranking, either partial or complete. The approach can be applied to support multicriteria choice and ranking of actions when the input information is a ranking of some reference actions.

Mining decision-rule preference model from rough approximation of preference relation

Greco, Salvatore;Matarazzo, Benedetto
2002-01-01

Abstract

Given a ranking of actions evaluated by a set of evaluation criteria, we are constructing a rough approximation of the preference relation known from this ranking. The rough approximation of the preference relation is a starting point for mining "if..., then..." decision rules constituting a symbolic preference model. The set of rules is induced such as to be compatible with a concordance discordance preference model used in well-known multicriteria decision aiding methods. Application of the set of decision rules to a new set of actions gives a fuzzy outranking graph. Positive and negative flows are calculated for each action in the graph, giving arguments about its strength and weakness. Aggregation of both arguments leads to a final ranking, either partial or complete. The approach can be applied to support multicriteria choice and ranking of actions when the input information is a ranking of some reference actions.
2002
0769517277
Software; Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/361682
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