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  4. Maschinelle Lernverfahren für nieder- und hochdimensionale Probleme
 

Maschinelle Lernverfahren für nieder- und hochdimensionale Probleme

URI
https://arbor.bfh.ch/handle/arbor/38105
Version
Published
Date Issued
2016-08-22
Author(s)
Type
Doctoral Thesis
Language
German
Abstract
In this habilitation thesis, problems in two different domains (record linkage and high-dimensional data) are addressed by using machine learning approaches. The assumption is that they lead to insights and solutions to which it would be difficult or even impossible to arrive with deterministic and classical statistical methods.
Arbor DOI
10.24451/arbor.13261
https://doi.org/10.24451/arbor.13261
Publisher URL
https://refubium.fu-berlin.de/handle/fub188/4721?show=full
Organization
Medicine
Charité - Universitätsmedizin Berlin
Institut für Medizininformatik I4MI  
Submitter
Sariyar, Murat
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e-habilschrift_sariyar_2016.pdf

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published
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