Rook, Cornelis Scipio Leeuwenhart (2025) Dynamic Bayesian networks for business data. Master's Thesis / Essay, Applied Mathematics.
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Abstract
Dynamic Bayesian networks (DBN) can be used to learn time-dependent relationships between variables. In the field of e-commerce, this was a relatively underexplored territory. Therefore, this thesis aimed to explore the applicability of the DBNs with a wide variety of experimental configurations to compare the effects of discretization, time delays and different structure learning methods. Moreover, a distance-based discretization method was included in addition to more conventional discretization methods because of its potential advantages in the e-commerce context. All in all, the thesis reports on the effects of the different experimental configurations and discusses their respective (dis)advantages in this context.
| Item Type: | Thesis (Master's Thesis / Essay) |
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| Supervisor name: | Grzegorczyk, M.A. and Krijnen, W.P. |
| Degree programme: | Applied Mathematics |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 19 Sep 2025 11:43 |
| Last Modified: | 19 Sep 2025 11:43 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/37030 |
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