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  • 标题:kernlab - An S4 Package for Kernel Methods in R
  • 本地全文:下载
  • 作者:Alexandros Karatzoglou ; Alexandros Smola ; Kurt Hornik
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2004
  • 卷号:11
  • 期号:1
  • 页码:1-20
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要: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.
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