|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:: 25103. Submitted: 2004-08-15. Published: 2004-11-02.
kernlab - An S4 Package for Kernel Methods in R
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.