Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/2329

 Title: Comparing Several Methods of Discriminant Analysis on the Case of Wine Data Authors: Vandev, DimitarRömisch, Ute Keywords: ApplicationLinear QuadraticDiscriminant AnalysisSVM Issue Date: 2004 Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences Citation: Pliska Studia Mathematica Bulgarica, Vol. 16, No 1, (2004), 299p-308p Abstract: The main problem of this European wine project (WINE-DB) is the identification of the geographical origin based on chemico-analytical measurements. At first the type of data collected in preparation of this project will be analysed. Then different procedures of Discriminant analysis are described. Our special attention will be focused to some new techniques as Support Vector Mashines (also known as Kernel Mashines) - procedures from the field of Mashine Learning. We test traditional techniques of Linear, Quadratic and Nonparametric Discriminant Analysis as well as the Support Vector Mashines on the base of our data and comment the results. Description: 2000 Mathematics Subject Classification: 62H30, 62J20, 62P12, 68T99 URI: http://hdl.handle.net/10525/2329 ISSN: 0204-9805 Appears in Collections: 2004 Volume 16

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