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Neural network ensembles
Thesis (MSc)--Stellenbosch University, 2004.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2012
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| _version_ | 1867613758182916096 |
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| access_status_str | Open Access |
| author | De Jongh, Albert |
| author2 | Cloete, Ian |
| author_browse | Cloete, Ian De Jongh, Albert |
| author_facet | Cloete, Ian De Jongh, Albert |
| author_sort | De Jongh, Albert |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2004. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/50035 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:41:12.661Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2012 |
| publishDateRange | 2012 |
| publishDateSort | 2012 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/50035 Neural network ensembles De Jongh, Albert Cloete, Ian Stellenbosch University. Faculty of Science. Dept. of Mathematical Sciences. Neural networks (Computer science) Set theory Bootstrap aggregating Boosting Dissertations -- Computer science Theses -- Computer science Dissertations -- Mathematical sciences Theses -- Mathematical sciences Thesis (MSc)--Stellenbosch University, 2004. ENGLISH ABSTRACT: It is possible to improve on the accuracy of a single neural network by using an ensemble of diverse and accurate networks. This thesis explores diversity in ensembles and looks at the underlying theory and mechanisms employed to generate and combine ensemble members. Bagging and boosting are studied in detail and I explain their success in terms of well-known theoretical instruments. An empirical evaluation of their performance is conducted and I compare them to a single classifier and to each other in terms of accuracy and diversity. AFRIKAANSE OPSOMMING: Dit is moontlik om op die akkuraatheid van 'n enkele neurale netwerk te verbeter deur 'n ensemble van diverse en akkurate netwerke te gebruik. Hierdie tesis ondersoek diversiteit in ensembles, asook die meganismes waardeur lede van 'n ensemble geskep en gekombineer kan word. Die algoritmes "bagging" en "boosting" word in diepte bestudeer en hulle sukses word aan die hand van bekende teoretiese instrumente verduidelik. Die prestasie van hierdie twee algoritmes word eksperimenteel gemeet en hulle akkuraatheid en diversiteit word met 'n enkele netwerk vergelyk. 2012-08-27T11:33:12Z 2012-08-27T11:33:12Z 2004-04 Thesis http://hdl.handle.net/10019.1/50035 en_ZA Stellenbosch University 104 leaves : ill. application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Neural networks (Computer science) Set theory Bootstrap aggregating Boosting Dissertations -- Computer science Theses -- Computer science Dissertations -- Mathematical sciences Theses -- Mathematical sciences De Jongh, Albert Neural network ensembles |
| title | Neural network ensembles |
| title_full | Neural network ensembles |
| title_fullStr | Neural network ensembles |
| title_full_unstemmed | Neural network ensembles |
| title_short | Neural network ensembles |
| title_sort | neural network ensembles |
| topic | Neural networks (Computer science) Set theory Bootstrap aggregating Boosting Dissertations -- Computer science Theses -- Computer science Dissertations -- Mathematical sciences Theses -- Mathematical sciences |
| url | http://hdl.handle.net/10019.1/50035 |
| work_keys_str_mv | AT dejonghalbert neuralnetworkensembles |