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Exploiting Sparse Dependence Structure in Model Based Classification
Dept. of Statistics, Stockholm University, Sweden.
2010 (English)In: COMBINING SOFT COMPUTING AND STATISTICAL METHODS IN DATA ANALYSIS / [ed] Borgelt, C; GonzalezRodriguez, G; Trutschnig, W; Lubiano, MA; Gil, MA; Grzegorzewski, P; Hryniewicz, O, 2010, 509-517 p.Conference paper (Refereed)
Abstract [en]

Sparsity patterns discovered in the data dependence structure were used to reduce the dimensionality and improve performance accuracy of the model based classifier in a high dimensional framework.

Place, publisher, year, edition, pages
2010. 509-517 p.
, Advances in Intelligent and Soft Computing, ISSN 1867-5662 ; 77
Keyword [en]
Classification, High dimensionality, Sparsity, Lasso, Variable selection
National Category
Natural Sciences
URN: urn:nbn:se:kth:diva-80818DOI: 10.1007/978-3-642-14746-3_63ISI: 000289216000063OAI: diva2:496775
1st International Workshop on Soft Methods in Probability and Statistics (SMPS 2002). WARSAW, POLAND. SEP, 2002
QC 20120302Available from: 2012-02-10 Created: 2012-02-10 Last updated: 2012-03-02Bibliographically approved

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Pavlenko, Tatjana
Natural Sciences

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