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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.