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ОбластМеки изчисленияМеки изчисления
СемействоMachine learningMachine learning
Година на възникване19972010
СъздателLotfi A. Zadeh (information granulation); developed by Pedrycz, Skowron, YaoYiyu Yao
ТипFramework for multi-granularity information processingDecision-theoretic classification framework
Основополагащ източникZadeh, 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 ↗Yao, Y. (2010). Three-way decisions with probabilistic rough sets. Information Sciences, 180(3), 341–353. DOI ↗
Други названияinformation granulation, computing with granules, three-way granular computing, tanecikli hesaplama3WD, Trisecting-and-Acting, Tri-partition Decision Making, Üç Yönlü Kararlar
Свързани32
РезюмеGranular 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.Three-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.
ScholarGateНабор от данни
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ScholarGateСравнение на методи: Granular Computing · Three-Way Decisions. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare