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DOI: 10.5445/IR/1000049548

Non-parametric Methods for Correlation Analysis in Multivariate Data with Applications in Data Mining

Nguyen, Hoang Vu

Abstract:
In this thesis, we develop novel methods for correlation analysis in multivariate data, with a special focus on mining correlated subspaces. Our methods handle major open challenges arisen when combining correlation analysis with subspace mining. Besides traditional correlation analysis, we explore interaction-preserving discretization of multivariate data and causality analysis. We conduct experiments on a variety of real-world data sets. The results validate the benefits of our methods.


Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Hochschulschrift
Jahr 2015
Sprache Englisch
Identifikator URN: urn:nbn:de:swb:90-495484
KITopen ID: 1000049548
Verlag Karlsruhe
Abschlussart Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Programmstrukturen und Datenorganisation (IPD)
Prüfungsdaten 06.02.2015
Referent/Betreuer Prof. K. Böhm
Schlagworte Non-parametric, Correlation Analysis, Multivariate Data, Data Mining
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