Asselt, J. van (2013) Many Layered Support Vector Machines. Bachelor's Thesis, Artificial Intelligence.
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Abstract
This thesis describes the expansion of the machine learning algorithm known as the two-layered Sup- port Vector Machine (SVM) (Wiering, Schutten, Millea, Meijster, and Schomaker, 2013) in order to improve the performance of this system. First, a de- scription of the standard SVM is given, followed by an overview of the two-layered SVM. Then another layer of SVMs is added to the two-layered SVM. The mathematical implications of this expansion will be described in detail. The metaparameters of the three-layered SVM are then found by using a combination of particle swarm optimisation and the UCB bandit algorithm. Experimental results show that the three-layered SVM outperforms a single- layered SVM. However, these results do not show an increase in performance compared to the two- layered SVM.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 15 Feb 2018 07:54 |
| Last Modified: | 15 Feb 2018 07:54 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/11248 |
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