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Authors: Alexandros Karatzoglou, Alexandros Smola, Kurt Hornik, Achim Zeileis
Title: [download]
(18985)
kernlab - An S4 Package for Kernel Methods in R
Reference: Vol. 11, Issue 9, Nov 2004
Submitted 2004-08-15, Accepted 2004-11-02
Type: Article
Abstract:

kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 ob ject 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.

Paper: [download]
(18985)
kernlab - An S4 Package for Kernel Methods in R
(application/pdf, 427.2 KB)
Supplements: [download]
(1424)
kernlab_0.4-1.tar.gz: R source package
(application/x-gzip, 855.3 KB)
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Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.
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