نتایج جستجو برای: non–additive robust ordinal regression
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Making any type of decision, from buying a car to siting a nuclear plant, from choosing the best student deserving a scholarship to ranking the cities of the world according to their liveability, involves the evaluation of several alternatives with respect to different aspects, technically called evaluation criteria. Multiple Criteria Decision Aiding (MCDA) (see [13, 14]) provides methodologies...
in most of the multi–criteria decision–analysis (mcda) problems in which the choquet integral is used as aggregation function, the coefficients of choquet integral (capacity) are not known in advance. actually, they could be calculated by capacity definition methods. in these methods, the preference information of decision maker (dm) is used to constitute a possible solution space. the methods ...
We introduce the principle of robust ordinal regression to group decision. We consider the main multiple criteria decision methods to which robust ordinal regression has been applied, i.e., UTA and GRIP methods, dealing with choice and ranking problems, UTADIS , dealing with sorting (ordinal classification) problems, and ELECTRE , being an outranking method applying robust ordinal regression to...
Robust regression is an appropriate alternative for ordinal regression when outliers exist in a given data set. If we have fuzzy observations, using ordinal regression methods can't model them; In this case, using fuzzy regression is a good method. When observations are fuzzy and there are outliers in the data sets, using robust fuzzy regression methods are appropriate alternatives....
Article history: Received 25 October 2010 Accepted 31 March 2011 Available online 8 April 2011
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