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Comparison between various regression depth methods and the support vector machine to approximate the minimum number of misclassifications

Title data

Christmann, Andreas ; Fischer, Paul ; Joachims, Thorsten:
Comparison between various regression depth methods and the support vector machine to approximate the minimum number of misclassifications.
In: Computational Statistics. Vol. 17 (2002) Issue 2 . - pp. 273-287.
ISSN 0943-4062
DOI: https://doi.org/10.1007/s001800200106

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
SFB-475: Reduction of Complexity in Multivariate Data StructuresNo information

Project financing: Deutsche Forschungsgemeinschaft
Deutsche Forschungsgemeinschaft

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics VII - Stochastics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics VII - Stochastics > Chair Mathematics VII - Stochastics - Univ.-Prof. Dr. Andreas Christmann
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
500 Science > 510 Mathematics
Date Deposited: 20 Oct 2015 07:17
Last Modified: 20 Oct 2015 07:17
URI: https://eref.uni-bayreuth.de/id/eprint/20558