The thesis considers a representation of a discrete multidimensional probability distribution using an apparatus of compositional models, and focuses on the theoretical background and structure of search space for structure learning algorithms in the framework of such models and particularly focuses on the subclass of decomposable models. Based on the theoretical results, proposals of basic learning techniques are introduced and compared.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:72677 |
| Date | January 2010 |
| Creators | Bína, Vladislav |
| Contributors | Jiroušek, Radim, Vomlelová, Marta, Řezanková, Hana |
| Publisher | Vysoká škola ekonomická v Praze |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.0031 seconds