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 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.
Year of publication: |
2004-11-02
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Authors: | Karatzoglou, Alexandros ; Smola, Alexandros ; Hornik, Kurt ; Zeileis, Achim |
Published in: |
Journal of Statistical Software. - American Statistical Association. - Vol. 11.2004, i09
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Publisher: |
American Statistical Association |
Saved in:
Saved in favorites
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