Titlebook: Rough Set–Based Classification Systems; Robert K. Nowicki Book 2019 Springer Nature Switzerland AG 2019 Rough Sets Theory.Computational In

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Final Remarks,put Inf Sci 11:341–356, 1982 [.]), Pawlak (Rough Sets: Theoretical Aspects of Reasoning About Data, Kluwer, Dordrecht, 1991 [.]), many extensions and modifications of this concept have been put forward Pal and Skowron (Rough-Fuzzy Hybridization: A New Trend in Decision Making. Springer, Berlin, Heid

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Book 2019pes of decisions, including those in which the information or input data is insufficient. Though decision-making and classification in cases with missing or inaccurate data is a common task, classical decision-making systems are not naturally adapted to it. One solution is to apply the rough set the

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Robert K. Nowickind die Manager dieser mit einem hohen Anteil an Fremdkapital vornehmlich in Produkte mit impliziter Hebelwirkung investierenden Investmentgesellschaften sind respektiert und gefürchtet. Denn einerseits erzielen einzelne Gesellschaften hohe überdurchschnittliche absolute Renditen, andererseits wird i

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Robert K. Nowickih an active market for replication—and alternative beta products. Its theoretical concepts were translated into market applications early on, generating wide interest among investors, even though the resulting products did not always perform to expectations. In Section 6.2 we comment on the evolutio

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Robert K. Nowickicorporate decisions. Instead, the system used to be controlled by a governing coalition consisting of controlling inside shareholders such as founding families and other companies, banks as the major providers of capital (Dittmann, Maug, and Schneider, 2010) and the company’s workforce. More recentl

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