4eMka2 is an implementation of the new approach in multiple criteria decision support, combining advantages of rough sets and dominance relation. The purpose of this system is resolving of multi-criteria sorting problems. System can be used in many different areas e.g. finances, medicine, geology, pharmacology and many other connected with analysis of vast data sets. The main difference between this system and the ones that are already in use is that it bases on rough set theory combined with dominance relation, which is quite new approach in multi-criteria decision support. The main function of the system is extraction of the classification rules from a set of already classified examples. These rules could be used to make partition of new data sets. Rules are presented in very convenient and comprehensible manner as a set of ”if ... then...” sentences. Another advantage of the system is dealing with inconsistent and incomplete data. This is possible due to use of rough set with dominance relation. The role of the user is simplified to preparation of the classified examples set and analysis of induced rules. It means that user stays within range of his domain. He does not have to get familiar with theory basis of used analysis model, which is often case in similar systems e.g. UTA and Electre. These systems do require much more skills from user at least to evaluate some additional coefficients. That means our system should be more user friendly and require less additional time spent to learn.

References in zbMATH (referenced in 41 articles )

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  1. Greco, Salvatore (ed.); Ehrgott, Matthias (ed.); Figueira, José Rui (ed.): Multiple criteria decision analysis. State of the art surveys. In 2 volumes (2016)
  2. Capotorti, Andrea; Barbanera, Eva: Credit scoring analysis using a fuzzy probabilistic rough set model (2012)
  3. Durbach, Ian N.; Stewart, Theodor J.: Modeling uncertainty in multi-criteria decision analysis (2012)
  4. Błaszczyński, Jerzy; Słowiński, Roman; Szeląg, Marcin: Sequential covering rule induction algorithm for variable consistency rough set approaches (2011)
  5. Fan, Tuan-Fang; Liau, Churn-Jung; Liu, Duen-Ren: Dominance-based fuzzy rough set analysis of uncertain and possibilistic data tables (2011)
  6. Miao, Duoqian; Gao, Can; Zhang, Nan; Zhang, Zhifei: Diverse reduct subspaces based co-training for partially labeled data (2011)
  7. Bouyssou, Denis; Marchant, Thierry: Additive conjoint measurement with ordered categories (2010)
  8. Greco, Salvatore; Matarazzo, Benedetto; Słowiński, Roman: Dominance-based rough set approach to decision under uncertainty and time preference (2010)
  9. Hu, Qinghua; Yu, Daren; Guo, Maozu: Fuzzy preference based rough sets (2010)
  10. Błaszczyński, Jerzy; Greco, Salvatore; Słowiński, Roman; Szelg, Marcin: Monotonic variable consistency rough set approaches (2009)
  11. Figueira, José Rui; Greco, Salvatore; Słowiński, Roman: Building a set of additive value functions representing a reference preorder and intensities of preference: GRIP method (2009)
  12. Inuiguchi, Masahiro; Yoshioka, Yukihiro; Kusunoki, Yoshifumi: Variable-precision dominance-based rough set approach and attribute reduction (2009)
  13. Mastrogiannis, Nikolaos; Boutsinas, Basilis; Giannikos, Ioannis: A method for improving the accuracy of data mining classification algorithms (2009)
  14. Roy, Bernard: On the meaning of dependencies between criteria: how should they be taken into account in decision making? (2009)
  15. Sawicki, Piotr; Ẓak, Jacek: Technical diagnostic of a fleet of vehicles using rough set theory (2009)
  16. Fortemps, Philippe; Greco, Salvatore; Słowiński, Roman: Multicriteria decision support using rules that represent rough-graded preference relations (2008)
  17. Greco, Salvatore; Mousseau, Vincent; Słowiński, Roman: Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions (2008)
  18. Mieszkowicz-Rolka, Alicja; Rolka, Leszek: Fuzzy rough approximations of process data (2008)
  19. Bouyssou, Denis; Marchant, Thierry: An axiomatic approach to noncompensatory sorting methods in MCDM. I: The case of two categories (2007)
  20. Bouyssou, Denis; Marchant, Thierry: An axiomatic approach to noncompensatory sorting methods in MCDM. II: M ore than two categories (2007)

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