Multiple kernel self-organizing maps

In a number of real-life applications, the user is interested in analyzing several sources of information together: a graph combined with the additional information known on its nodes, numerical variables measured on individuals and factors describing these individuals... The combination of all sour...

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Main Authors Olteanu , Madalina (INRA (France). ), Villa-Vialaneix , Nathalie (INRA , Auzeville (France). UR 0875 Mathématiques et Informatique Appliquées Toulouse ), Cierco-Ayrolles , Christine (INRA , Nantes (France). UR 1268 Biopolymères, Interactions Assemblages)
Format Conference Proceeding
LanguageEnglish
Published 2013
Subjects
analyse de données
autoorganisation
carte
graph
kernel
self-organizing map
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Summary:In a number of real-life applications, the user is interested in analyzing several sources of information together: a graph combined with the additional information known on its nodes, numerical variables measured on individuals and factors describing these individuals... The combination of all sources of information can help him to understand the dataset in its whole better. The present article focuses on such an issue, by using self-organizing maps. The use a kernel version of the algorithm allows us to combine various types of information and automatically tune the data combination. This approach is illustrated on a simulated example.
Bibliography:2014053511