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kernlab - An S4 package for kernel methods in R

kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 object model and provides a framework for creating and using kernel-based algorithms. The package contains dot product primitives (kernels), implementations of support vector machines and the relevance vector machine, Gaussian processes, a ranking algorithm, kernel PCA, kernel CCA, and a spectral clustering algorithm. Moreover it provides a general purpose quadratic programming solver, and an incomplete Cholesky decomposition method. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_766
Date January 2004
CreatorsKaratzoglou, Alexandros, Smola, Alex, Hornik, Kurt, Zeileis, Achim
PublisherInstitut fĂĽr Statistik und Mathematik, WU Vienna University of Economics and Business
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypePaper, NonPeerReviewed
Formatapplication/pdf
Relationhttp://epub.wu.ac.at/1048/

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