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	Višekriterijumska analiza odlučivanja vođena podacima	ELECTRE I	Tehnika za redosled preferencija po sličnosti sa idealnim rešenjem
Oblast	Donošenje odluka	Donošenje odluka	Donošenje odluka
Porodica	MCDM	MCDM	MCDM
Godina nastanka	2015	1968	1981
Tvorac	Multiple authors	Roy, B.	Hwang, C. L., Yoon, K.
Tip	Learning-based criteria weighting and aggregation	Concordance–discordance (crisp outranking)	Distance-based (compromise)
Temeljni izvor	Греченко, Д. В. (2019). Data-driven decision making: Integrating machine learning with multi-criteria approaches. Computational Statistics & Data Analysis, 132, 127-143.	Roy, B. (1968). Classement et choix en présence de points de vue multiples (la méthode ELECTRE). Revue Française d'Informatique et de Recherche Opérationnelle	Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications — A State-of-the-Art Survey. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag
Drugi nazivi	Data-Driven MCDA	—	—
Srodne	5	8	8
Sažetak	Data-Driven MCDA is a hybrid framework that integrates machine learning and statistical learning into traditional multi-criteria decision analysis. Instead of eliciting weights from expert judgment, it learns criteria importance from historical decision data, enabling more scalable and empirically grounded decision support.	ELECTRE (ELECTRE I — ELimination Et Choix Traduisant la REalité) is a outranking multi-criteria decision-making (MCDM) method introduced by Roy, B. in 1968. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.