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	Knowledge Discovery from Databases with Use of the R Language Krutý, Peter ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor) This thesis is focused on the field of knowledge discovery from databases. Main objective is to research possibilities of R language and its support in this area. Support is researched by experiments using appropriate data sets. More detailed attention is given to the methods of classification, clustering and association rules learning. The output of the thesis is comparison of methods application in R and defining the suitability of using language for knowledge discovery from databases. Detailed record
	Knowledge Discovery from Databases with Use of the R Language Krutý, Peter ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor) This thesis is focused on the field of knowledge discovery from databases. Main objective is to research possibilities of R language and its support in this area. Support is researched by experiments using appropriate data sets. More detailed attention is given to the methods of classification, clustering and association rules learning. The output of the thesis is comparison of methods application in R and defining the suitability of using language for knowledge discovery from databases. Detailed record
	Nonlinear regression in R programming langure Dolák, Martin ; Malá, Ivana (advisor) ; Bašta, Milan (referee) This thesis deals with solutions of nonlinear regression problems using R programming language. The introductory theoretical part is devoted to familiarization with the principles of solving nonlinear regression models and of their applications in the program R. In both, theoretical and practical part, the most famous and used differentiator algorithms are presented, particularly the Gauss-Newton's and of the steepest descent method, for estimating the parameters of nonlinear regression. Further, in the practical part, there are some demo solutions of particular tasks using nonlinear regression methods. Overall, a large number of graphs processed by the author is used in this thesis for better comprehension. Detailed record

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