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ОбластМеки изчисленияМеки изчисления
СемействоMachine learningMachine learning
Година на възникване20101997
СъздателYiyu YaoLotfi A. Zadeh (information granulation); developed by Pedrycz, Skowron, Yao
ТипDecision-theoretic classification frameworkFramework for multi-granularity information processing
Основополагащ източникYao, Y. (2010). Three-way decisions with probabilistic rough sets. Information Sciences, 180(3), 341–353. DOI ↗Zadeh, L. A. (1997). Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems, 90(2), 111–127. DOI ↗
Други названия3WD, Trisecting-and-Acting, Tri-partition Decision Making, Üç Yönlü Kararlarinformation granulation, computing with granules, three-way granular computing, tanecikli hesaplama
Свързани23
РезюмеThree-Way Decisions (3WD) is a decision-theoretic framework, introduced by Yiyu Yao in 2010, that partitions the universe of objects into three regions—positive (accept), negative (reject), and boundary (abstain)—using probabilistic rough set theory. Unlike binary classifiers that force every object into one of two classes, 3WD explicitly acknowledges uncertainty by allowing a third option: deferring judgment when available evidence is insufficient for a confident decision.Granular computing is a problem-solving paradigm that processes information in 'granules' — clumps of objects drawn together by indistinguishability, similarity, or functionality — rather than at the level of individual data points. Articulated by Lotfi Zadeh in 1997 as fuzzy information granulation and developed into a broad framework, it provides a unifying umbrella over fuzzy sets, rough sets, and interval methods, letting analysis move to whichever level of detail a problem actually requires.
ScholarGateНабор от данни
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ScholarGateСравнение на методи: Three-Way Decisions · Granular Computing. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare