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A Proposal of Machine Learning by Rule Generation from Tables with Non-deterministic Information and Its Prototype System.

, , and . IJCRS (1), volume 10313 of Lecture Notes in Computer Science, page 535-551. Springer, (2017)

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Semantic field as a bridge between data and decision., , and . KES, page 589-593. IEEE, (2000)Properties on inclusion relations and division charts in non-deterministic information systems., , , and . GrC, page 521-526. IEEE Computer Society, (2011)Lower and Upper Approximations in Data Tables Containing Possibilistic Information., and . Trans. Rough Sets, (2007)An overview of decision making in Rough Non-deterministic Information Analysis., , , and . NaBIC, page 345-350. IEEE, (2010)Association rule-based decision making in table data., , and . IJRIS, 4 (3): 162-170 (2012)Rule Generation in Lipski's Incomplete Information Databases., , and . RSCTC, volume 6086 of Lecture Notes in Computer Science, page 376-385. Springer, (2010)Functional Dependencies in Relational Expressions Based on Or-Sets., and . Rough Sets and Current Trends in Computing, volume 2475 of Lecture Notes in Computer Science, page 161-166. Springer, (2002)Checking Whether or Not Rough-Set-Based Methods to Incomplete Data Satisfy a Correctness Criterion., and . MDAI, volume 3558 of Lecture Notes in Computer Science, page 227-239. Springer, (2005)Rough Sets and Rule Induction by an Approach Based on Coverings in Information Tables., , , and . J. Multiple Valued Log. Soft Comput., 39 (5-6): 463-484 (2022)A Prototype System for Rule Generation in Lipski's Incomplete Information Databases., , and . RSFDGrC, volume 6743 of Lecture Notes in Computer Science, page 175-182. Springer, (2011)