Comparing Several Methods of Discriminant Analysis on the Case of Wine Data
Data(s) |
23/02/2014
23/02/2014
2004
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Resumo |
2000 Mathematics Subject Classification: 62H30, 62J20, 62P12, 68T99 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. Partially supported by contracts: PRO-ENBIS: GTC1-2001-43031 and WINE DB: G6RDCT-2001-00646. |
Identificador |
Pliska Studia Mathematica Bulgarica, Vol. 16, No 1, (2004), 299p-308p 0204-9805 |
Idioma(s) |
en |
Publicador |
Institute of Mathematics and Informatics Bulgarian Academy of Sciences |
Palavras-Chave | #Application #Linear Quadratic #Discriminant Analysis #SVM |
Tipo |
Article |