Who Cited It

kernlab - An S4 Package for Kernel Methods in R

2004 · Journal of Statistical Software · 1,864 citations · 0 from inside this corpus

Alexandros Karatzoglou, Alex Smola, Kurt Hornik, Achim Zeileis

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.

kernlab - An S4 Package for Kernel Methods in R (2004)kernlab - An S4 Package for K…The Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…Statistical Learning Theory (1999)Statistical Learning TheoryNonlinear Component Analysis as a Kernel Eigenvalue Problem (1998)Nonlinear Component Analysis …Estimating the Support of a High-Dimensional Distribution (2001)Estimating the Support of a H…Advances in kernel methods: support vector learning (1999)Advances in kernel methods: s…Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho… (1999)Probabilistic Outputs for Sup…Making Large-Scale SVM Learning Practical (2006)Making Large-Scale SVM Learni…Learning with Kernels (2001)Learning with KernelsSupport vector domain description (1999)Support vector domain descrip…
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What this paper cites, inside the corpus

PaperYearCited
The Nature of Statistical Learning Theory199539,409
Statistical Learning Theory199926,957
Nonlinear Component Analysis as a Kernel Eigenvalue Problem19988,138
Estimating the Support of a High-Dimensional Distribution20016,097
Advances in kernel methods: support vector learning19995,819
Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho…19994,873
Making Large-Scale SVM Learning Practical20064,326
Learning with Kernels20012,541
Support vector domain description19991,626

Links

DOI · Open access copy · OpenAlex record

Topics

Gaussian Processes and Bayesian InferenceComputer Science
Neural Networks and ApplicationsComputer Science
Time Series Analysis and ForecastingComputer Science

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complete

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  • supports4 author record(s) attached.
  • supports28 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

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