Discriminant analysis : a review of its application to the classificationof grape cultivars

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dc.contributor.advisorZucchini, Walteren_ZA
dc.contributor.advisorStewart, Theodor Jen_ZA
dc.contributor.authorBlignaut, Rennette Juliaen_ZA
dc.date.accessioned2015-10-25T17:00:46Z
dc.date.available2015-10-25T17:00:46Z
dc.date.issued1989en_ZA
dc.description.abstractThe aim of this study was to calculate a classification function for discriminating between five grape cultivars with a view to determine the cultivar of an unknown grape juice. In order to discriminate between the five grape cultivars various multivariate statistical techniques, such as principal component analysis, cluster analysis, correspondence analysis and discriminant analysis were applied. Discriminant analysis resulted in the most appropriate technique for the problem at hand and therefore an in depth study of this technique was undertaken. Discriminant analysis was the most appropriate technique for classifying these grape samples into distinct cultivars because this technique utilized prior information of population membership. This thesis is divided into two main sections. The first section (chapters 1 to 5) is a review on discriminant analysis, describing various aspects of this technique and matters related thereto. In the second section (chapter 6) the theories discussed in the first section are applied to the problem at hand. The results obtained when discriminating between the different grape cultivars are given. Chapter 1 gives a general introduction to the subject of discriminant analysis, including certain basic derivations used in this study. Two approaches to discriminant analysis are discussed in Chapter 2, namely the parametrical and non-parametrical approaches. In this review the emphasis is placed on the classical approach to discriminant analysis. Non-parametrical approaches such as the K-nearest neighbour technique, the kernel method and ranking are briefly discussed. Chapter 3 deals with estimating the probability of misclassification. In Chapter 4 variable selection techniques are discussed. Chapter 5 briefly deals with sequential and logistical discrimination techniques. The estimation of missing values is also discussed in this chapter. A final summary and conclusion is given in Chapter 7. Appendices A to D illustrate some of the obtained results from the practical analyses.en_ZA
dc.identifier.apacitationBlignaut, R. J. (1989). <i>Discriminant analysis : a review of its application to the classificationof grape cultivars</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/14298en_ZA
dc.identifier.chicagocitationBlignaut, Rennette Julia. <i>"Discriminant analysis : a review of its application to the classificationof grape cultivars."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 1989. http://hdl.handle.net/11427/14298en_ZA
dc.identifier.citationBlignaut, R. 1989. Discriminant analysis : a review of its application to the classificationof grape cultivars. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Blignaut, Rennette Julia AB - The aim of this study was to calculate a classification function for discriminating between five grape cultivars with a view to determine the cultivar of an unknown grape juice. In order to discriminate between the five grape cultivars various multivariate statistical techniques, such as principal component analysis, cluster analysis, correspondence analysis and discriminant analysis were applied. Discriminant analysis resulted in the most appropriate technique for the problem at hand and therefore an in depth study of this technique was undertaken. Discriminant analysis was the most appropriate technique for classifying these grape samples into distinct cultivars because this technique utilized prior information of population membership. This thesis is divided into two main sections. The first section (chapters 1 to 5) is a review on discriminant analysis, describing various aspects of this technique and matters related thereto. In the second section (chapter 6) the theories discussed in the first section are applied to the problem at hand. The results obtained when discriminating between the different grape cultivars are given. Chapter 1 gives a general introduction to the subject of discriminant analysis, including certain basic derivations used in this study. Two approaches to discriminant analysis are discussed in Chapter 2, namely the parametrical and non-parametrical approaches. In this review the emphasis is placed on the classical approach to discriminant analysis. Non-parametrical approaches such as the K-nearest neighbour technique, the kernel method and ranking are briefly discussed. Chapter 3 deals with estimating the probability of misclassification. In Chapter 4 variable selection techniques are discussed. Chapter 5 briefly deals with sequential and logistical discrimination techniques. The estimation of missing values is also discussed in this chapter. A final summary and conclusion is given in Chapter 7. Appendices A to D illustrate some of the obtained results from the practical analyses. DA - 1989 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1989 T1 - Discriminant analysis : a review of its application to the classificationof grape cultivars TI - Discriminant analysis : a review of its application to the classificationof grape cultivars UR - http://hdl.handle.net/11427/14298 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/14298
dc.identifier.vancouvercitationBlignaut RJ. Discriminant analysis : a review of its application to the classificationof grape cultivars. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 1989 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/14298en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Statistical Sciencesen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherMathematical Statisticsen_ZA
dc.titleDiscriminant analysis : a review of its application to the classificationof grape cultivarsen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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