Comparing Several Methods of Discriminant Analysis on the Case of Wine Data


Autoria(s): Vandev, Dimitar; Römisch, Ute
Data(s)

23/02/2014

23/02/2014

2004

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

http://hdl.handle.net/10525/2329

Idioma(s)

en

Publicador

Institute of Mathematics and Informatics Bulgarian Academy of Sciences

Palavras-Chave #Application #Linear Quadratic #Discriminant Analysis #SVM
Tipo

Article