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Discriminant analysis : a review of its application to the classificationof grape cultivars
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 c...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2015
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| _version_ | 1867613241927008256 |
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| access_status_str | Open Access |
| author | Blignaut, Rennette Julia |
| author2 | Zucchini, Walter |
| author_browse | Blignaut, Rennette Julia Zucchini, Walter |
| author_facet | Zucchini, Walter Blignaut, Rennette Julia |
| author_sort | Blignaut, Rennette Julia |
| collection | Thesis |
| description | 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. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/14298 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:01.081Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/14298 Discriminant analysis : a review of its application to the classificationof grape cultivars Blignaut, Rennette Julia Zucchini, Walter Stewart, Theodor J Mathematical Statistics 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. 2015-10-25T17:00:46Z 2015-10-25T17:00:46Z 1989 Master Thesis Masters MSc http://hdl.handle.net/11427/14298 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Mathematical Statistics Blignaut, Rennette Julia Discriminant analysis : a review of its application to the classificationof grape cultivars |
| thesis_degree_str | Master's |
| title | Discriminant analysis : a review of its application to the classificationof grape cultivars |
| title_full | Discriminant analysis : a review of its application to the classificationof grape cultivars |
| title_fullStr | Discriminant analysis : a review of its application to the classificationof grape cultivars |
| title_full_unstemmed | Discriminant analysis : a review of its application to the classificationof grape cultivars |
| title_short | Discriminant analysis : a review of its application to the classificationof grape cultivars |
| title_sort | discriminant analysis a review of its application to the classificationof grape cultivars |
| topic | Mathematical Statistics |
| url | http://hdl.handle.net/11427/14298 |
| work_keys_str_mv | AT blignautrennettejulia discriminantanalysisareviewofitsapplicationtotheclassificationofgrapecultivars |