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Simultaneous clustering with mixtures of factor analysers
This work details the method of Simultaneous Model-based Clustering. It also presents an extension to this method by reformulating it as a model with a mixture of factor analysers. This allows for the technique, known as Simultaneous Model-Based Clustering with a Mixture of Factor Analysers, to be a...
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| Format: | Thesis |
| Language: | English |
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Department of Medicine
2015
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| _version_ | 1867613178147373056 |
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| access_status_str | Open Access |
| author | O'Donnell, Warwick |
| author2 | Lesosky, Maia |
| author_browse | Lesosky, Maia O'Donnell, Warwick |
| author_facet | Lesosky, Maia O'Donnell, Warwick |
| author_sort | O'Donnell, Warwick |
| collection | Thesis |
| description | This work details the method of Simultaneous Model-based Clustering. It also presents an extension to this method by reformulating it as a model with a mixture of factor analysers. This allows for the technique, known as Simultaneous Model-Based Clustering with a Mixture of Factor Analysers, to be able to cluster high dimensional gene-expression data. A new table of allowable and non-allowable models is formulated, along with a parameter estimation scheme for one such allowable model. Several numerical procedures are tested and various datasets, both real and generated, are clustered. The results of clustering the Iris data find a 3 component VEV model to have the lowest misclassification rate with comparable BIC values to the best scoring model. The clustering of Genetic data was less successful, where the 2-component model could successfully uncover the healthy tissue, but partitioned the cancerous tissue in half. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/13972 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:00.945Z |
| 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 Medicine |
| publisherStr | Department of Medicine |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/13972 Simultaneous clustering with mixtures of factor analysers O'Donnell, Warwick Lesosky, Maia Medicine This work details the method of Simultaneous Model-based Clustering. It also presents an extension to this method by reformulating it as a model with a mixture of factor analysers. This allows for the technique, known as Simultaneous Model-Based Clustering with a Mixture of Factor Analysers, to be able to cluster high dimensional gene-expression data. A new table of allowable and non-allowable models is formulated, along with a parameter estimation scheme for one such allowable model. Several numerical procedures are tested and various datasets, both real and generated, are clustered. The results of clustering the Iris data find a 3 component VEV model to have the lowest misclassification rate with comparable BIC values to the best scoring model. The clustering of Genetic data was less successful, where the 2-component model could successfully uncover the healthy tissue, but partitioned the cancerous tissue in half. 2015-09-15T10:24:43Z 2015-09-15T10:24:43Z 2013 Master Thesis Masters MSc (Med) http://hdl.handle.net/11427/13972 eng application/pdf Department of Medicine Faculty of Health Sciences University of Cape Town |
| spellingShingle | Medicine O'Donnell, Warwick Simultaneous clustering with mixtures of factor analysers |
| thesis_degree_str | Master's |
| title | Simultaneous clustering with mixtures of factor analysers |
| title_full | Simultaneous clustering with mixtures of factor analysers |
| title_fullStr | Simultaneous clustering with mixtures of factor analysers |
| title_full_unstemmed | Simultaneous clustering with mixtures of factor analysers |
| title_short | Simultaneous clustering with mixtures of factor analysers |
| title_sort | simultaneous clustering with mixtures of factor analysers |
| topic | Medicine |
| url | http://hdl.handle.net/11427/13972 |
| work_keys_str_mv | AT odonnellwarwick simultaneousclusteringwithmixturesoffactoranalysers |