Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
Zur Ablage hinzufügen
 Lokale TagsFreigabegeschichteDetailsÜbersicht
  Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge

Chapelle, O. (2004). Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge. PhD Thesis, Universit ́e Pierre et Marie Curie: Paris VI, Paris, France.

Item is

 

einblenden: alle

Basisdaten

ausblenden:
Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E13F-6 Versions-Permalink: https://hdl.handle.net/21.11116/0000-0005-9E34-F
Genre: Hochschulschrift

Externe Referenzen

ausblenden:
externe Referenz:
http://olivier.chapelle.cc/pub/thesis.pdf (beliebiger Volltext)
Beschreibung:
-
OA-Status:

Urheber

ausblenden:
 Urheber:
Chapelle, O1, 2, Autor           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Inhalt

ausblenden:
Schlagwörter: -
 Zusammenfassung: This thesis presents a theoretical and practical study of Support
Vector Machines (SVM) and related learning algorithms. In a first part,
we introduce a new induction principle from which SVMs can be derived, but
some new algorithms are also presented in this framework.
In a second part, after studying how to estimate the generalization
error of an SVM, we suggest to choose the kernel parameters of an SVM
by minimizing this estimate. Several applications such as feature
selection are presented. Finally the third part deals with the incoporation
of prior knowledge in a learning algorithm and more specifically, we
studied the case of known invariant transormations and the use
of unlabeled data.

Details

ausblenden:
Sprache(n):
 Datum: 2002-062004-04
 Publikationsstatus: Erschienen
 Seiten: 180
 Ort, Verlag, Ausgabe: Paris, France : Universit ́e Pierre et Marie Curie: Paris VI
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: 2167
 Art des Abschluß: Doktorarbeit

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle

einblenden: