Data Mining with Graphical Models
dc.contributor.author | Kruse, Rudolf | |
dc.contributor.author | Borgelt, Christian | |
dc.contributor.editor | Haasis, H.-D. | |
dc.contributor.editor | Ranze, K.C. | |
dc.date.accessioned | 2019-09-16T09:30:50Z | |
dc.date.available | 2019-09-16T09:30:50Z | |
dc.date.issued | 1998 | |
dc.description.abstract | The explosion of data stored in commercial or administrational databases calls for intelligent techniques to discover the patterns hidden in them and thus to exploit all available information. Therefore a new line of research has recently been established, which became known under the names "Data Mining" and "Knowledge Discovery in Databases". In this paper we study a popular technique from its arsenal of methods to do dependency analysis, namely learning inference networks (also called "graphical models") from data. We review the already well-known probabilistic networks and provide an introduction to the recently developed and closely related possibilistic networks. | de |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/26495 | |
dc.publisher | Metropolis | |
dc.relation.ispartof | Umweltinformatik ’98 - Vernetzte Strukturen in Informatik, Umwelt und Wirtschaft - Computer Science for Environmental Protection ’98 - Networked Structures in Information Technology, the Environment and Business | |
dc.relation.ispartofseries | EnviroInfo | |
dc.title | Data Mining with Graphical Models | de |
dc.type | Text/Conference Paper | |
gi.citation.publisherPlace | Marburg | |
gi.conference.date | 1998 | |
gi.conference.location | Bremen | |
gi.conference.sessiontitle | Eingeladene Hauptvorträge; Invited Lectures |