kernlab - An S4 Package for Kernel Methods in R

Alexandros Karatzoglou, Alexandros Smola, Kurt Hornik and Achim Zeileis ()

Journal of Statistical Software, 2004, vol. 011, issue i09

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.

Date: 2004-11-02
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Citations: View citations in EconPapers (85)

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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:011:i09

DOI: 10.18637/jss.v011.i09

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