Lattice Theory for Machine Learning
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Published:2022-12
Issue:5
Volume:49
Page:379-384
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ISSN:0147-6882
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Container-title:Scientific and Technical Information Processing
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language:en
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Short-container-title:Sci. Tech. Inf. Proc.
Subject
General Computer Science
Reference10 articles.
1. Finn, V.K., J.S. Mill’s inductive methods in artificial intelligence systems. Part I, Sci. Tech. Inf. Process., 2011, vol. 38, no. 6, pp. 385–402. https://doi.org/10.3103/S0147688211060037 2. Finn, V.K., J.S. Mill’s inductive methods in artificial intelligence systems. Part II, Sci. Tech. Inf. Process., 2012, vol. 39, no. 5, pp. 241–260. https://doi.org/10.3103/S0147688212050036 3. Kuznetsov, S.O., On computing the size of a lattice and related decision problems, Order, 2001, vol. 18, no. 4, pp. 313–321. https://doi.org/10.1023/A:1013970520933 4. Vinogradov, D.V., Machine learning based on similarity operation, Artificial Intelligence. RCAI 2018, Kuznetsov, S., Osipov, G., and Stefanuk, V., Eds., Communications in Computer and Information Science, vol. 934, Cham: Springer, 2018, pp. 46–59. https://doi.org/10.1007/978-3-030-00617-4_5 5. Ganter, B. and Wille, R., Formal Concept Analysis: Mathematical Foundations, Berlin: Springer, 1999. https://doi.org/10.1007/978-3-642-59830-2
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