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An Experimental Comparison of Three Probabilistic Approximations Used for Rule Induction., и . Fundam. Informaticae, 127 (1-4): 177-191 (2013)Three discretization methods for rule induction., и . Int. J. Intell. Syst., 16 (1): 29-38 (2001)A comparison of three closest fit approaches to missing attribute values in preterm birth data., , и . Int. J. Intell. Syst., 17 (2): 125-134 (2002)On partitions of the state set and relations in the input semigroup of automata (Russian).. Elektronische Informationsverarbeitung und Kybernetik, 11 (10-12): 581-582 (1975)Complexity of Rule Sets Induced from Incomplete Data with Attribute-concept Values and "Do Not Care" Conditions., и . DATA, стр. 56-63. SciTePress, (2014)Complexity of Rule Sets Induced from Incomplete Data Sets Using Global Probabilistic Approximations., и . IPMU (1), том 442 из Communications in Computer and Information Science, стр. 386-395. Springer, (2014)Rule Induction from Rough Approximations.. Handbook of Computational Intelligence, Springer, (2015)The Usefulness of a Machine Learning Approach to Knowledge Acquisition., и . Comput. Intell., (1995)A Rough Set Approach to Incomplete Data.. RSKT, том 9436 из Lecture Notes in Computer Science, стр. 3-14. Springer, (2015)Mining Incomplete Data with Attribute-Concept Values and "Do Not Care" Conditions., и . HAIS, том 8480 из Lecture Notes in Computer Science, стр. 156-167. Springer, (2014)