Learning topology of a labeled data set with the supervised generative gaussian graph

Gaillard Pierre, Aupetit Michaël, Govaert Gérard

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Discovering the topology of a set of labeled data in a Euclidian space can help to design better decision systems. In this work, we propose a supervised generative model based on the Delaunay Graph of some prototypes representing the labeled data.

Original languageEnglish
Title of host publicationESANN 2007 Proceedings - 15th European Symposium on Artificial Neural Networks
Pages235-240
Number of pages6
Publication statusPublished - 2007
Externally publishedYes
Event15th European Symposium on Artificial Neural Networks, ESANN 2007 - Bruges, Belgium
Duration: 25 Apr 200727 Apr 2007

Publication series

NameESANN 2007 Proceedings - 15th European Symposium on Artificial Neural Networks

Conference

Conference15th European Symposium on Artificial Neural Networks, ESANN 2007
Country/TerritoryBelgium
CityBruges
Period25/04/0727/04/07

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