2022

chapter in monograph

english

EN Dominance-based Rough Set Approach (DRSA) has been proposed as a machine learning and knowledge discovery methodology to handle Multiple Criteria Decision Aiding (MCDA). Due to its capacity of asking the decision maker (DM) for simple preference information and supplying easily understandable and explainable recommendations, DRSA gained much interest during the years and it is now one of the most appreciated MCDA approaches. In fact, it has been applied also beyond MCDA domain, as a general knowledge discovery and data mining methodology for the analysis of monotonic (and also non-monotonic) data. In this contribution, we recall the basic principles and the main concepts of DRSA, with a general overview of its developments and software. We present also a historical reconstruction of the genesis of this methodology, with a specific focus on the contribution of Roman Słowiński.

09.02.2022

353 - 382

10.1007/978-3-030-96318-7_18

https://link.springer.com/chapter/10.1007/978-3-030-96318-7_18

Intelligent Decision Support Systems : Combining Operations Research and Artificial Intelligence - Essays in Honor of Roman Słowiński

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