Authors: | Alexandros Karatzoglou, Alexandros Smola, Kurt Hornik, Achim Zeileis | ||
Title: | kernlab - An S4 Package for Kernel Methods in R | ||
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. | ||
Page views:: 27523. Submitted: 2004-08-15. Published: 2004-11-02. |
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Paper: |
kernlab - An S4 Package for Kernel Methods in R
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DOI: |
10.18637/jss.v011.i09
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![]() 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. |