kernlab - An S4 package for kernel methods in R

Karatzoglou, Alexandros and Smola, Alex and Hornik, Kurt and Zeileis, Achim (2004) kernlab - An S4 package for kernel methods in R. Research Report Series / Department of Statistics and Mathematics, 9. Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, Vienna.

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kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 object 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. (author's abstract)

Item Type: Paper
Keywords: kernel methods / support vector machines / quadratic programming / ranking / clustering / S4 / R
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 24 Aug 2004 11:27
Last Modified: 22 Oct 2019 00:41

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