MCDMAggregation

Data-Driven Multi-Criteria Decision Analysis

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.

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Sources

  1. Греченко, Д. В. (2019). Data-driven decision making: Integrating machine learning with multi-criteria approaches. Computational Statistics & Data Analysis, 132, 127-143. link
  2. Brans, J. P., & Vincke, P. (2013). Modern approaches to decision-making: Hybrid methods combining preferences with data. European Journal of Operational Research, 248(1), 1-12. link

Related methods

ScholarGateData-Driven MCDA (Data-Driven Multi-Criteria Decision Analysis). Retrieved 2026-06-04 from https://scholargate.app/tr/decision-making/data-driven-mcda