Ensemble classification and its application to visual tracking
In machine learning and statistics, ensemble methods employ multiple models to obtain better performance than that could be obtained from any of the constituent (base) models [1]. Many studies have been published, both theoretical and empirical, which demonstrate the advantages of ensemble methods f...
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Online Access: | https://hdl.handle.net/10356/69073 |
| Summary: | In machine learning and statistics, ensemble methods employ multiple models to obtain better performance than that could be obtained from any of the constituent (base) models [1]. Many studies have been published, both theoretical and empirical, which demonstrate the advantages of ensemble methods for classification. |
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