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.

• Publication year

  2004

• Venue

  Journal of Statistical Software

• Publication date

  2004-11-02

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.18637/JSS.V011.I09
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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