Reference : Robustness analysis of clustering and classification techniques

	Document type :	Dissertations and theses : Doctoral thesis
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Mathematics
	To cite this reference:	http://hdl.handle.net/2268/119808

Title :	Robustness analysis of clustering and classification techniques
Language :	English
Author, co-author :	Ruwet, Christel [Université de Liège - ULg > Département de mathématique > Statistique mathématique >]
Publication date :	8-Jun-2012
Institution :	Université de Liège
Name of the degree :	Docteur en Sciences
Country :	Belgique
Superviser :	Haesbroeck, Gentiane
	Garcia-Escudero, Luis Angel
President of the jury :	Albert, Adelin
Member of the jury :	Heuchenne, Cédric
	Croux, Christophe
	Dehon, Catherine
	Gordaliza, Alfonso
Keywords :	[en] Clustering ; Classification ; Error rate ; Breakdown point ; Influence function ; Robustness
Abstract :	[en] As mentioned in the title, the framework of this doctoral dissertation encompasses two different subjects: robust statistics on the one hand and classification and clustering techniques on the other hand. Robust procedures try at the same time to emulate classical procedures and to produce results that are not unduly affected by contaminated observations or deviations from model assumptions. Classification and clustering techniques try to find groups among observations. Grouping is one of the most basic abilities of living creatures; the simple fact of naming objects is already grouping. The main interest lies in the fact that the characteristics of a group as well as its differences from other groups can be used as a summary of the dataset.
Permalink :	http://hdl.handle.net/2268/119808

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	Fulltext file(s): File Commentary Version Size Access Restricted access These.pdf Author preprint 2.52 MB Request copy Additional material(s): File Commentary Version Size Access Restricted access DefenseBis.pdf Slides de la défense - 1.04 MB Request copy Restricted access Erratum.pdf Erratum - 31.26 kB Request copy

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