Salīdzināt metodes

	Lēmumi trīs daļās	Granulārā skaitļošana (informācijas granulēšana)
Nozare	Mīkstā skaitļošana	Mīkstā skaitļošana
Saime	Machine learning	Machine learning
Izcelsmes gads	2010	1997
Autors	Yiyu Yao	Lotfi A. Zadeh (information granulation); developed by Pedrycz, Skowron, Yao
Tips	Decision-theoretic classification framework	Framework for multi-granularity information processing
Pirmavots	Yao, Y. (2010). Three-way decisions with probabilistic rough sets. Information Sciences, 180(3), 341–353.	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.
Citi nosaukumi	3WD, Trisecting-and-Acting, Tri-partition Decision Making, Üç Yönlü Kararlar	information granulation, computing with granules, three-way granular computing, tanecikli hesaplama
Saistītās	2	3
Kopsavilkums	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.	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.