kernlab: Kernel-based Machine Learning Lab

Kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA and a QP solver.

Version: 0.9-14
Depends: R (≥ 2.10), methods
Published: 2011-11-02
Author: Alexandros Karatzoglou, Alex Smola, Kurt Hornik
Maintainer: Alexandros Karatzoglou <alexis at ci.tuwien.ac.at>
License: GPL-2
Citation: kernlab citation info
In views: Cluster, MachineLearning, Multivariate, NaturalLanguageProcessing, Optimization
CRAN checks: kernlab results

Downloads:

Package source: kernlab_0.9-14.tar.gz
MacOS X binary: kernlab_0.9-14.tgz
Windows binary: kernlab_0.9-14.zip
Reference manual: kernlab.pdf
Vignettes: kernlab - An S4 Package for Kernel Methods in R
Old sources: kernlab archive

Reverse dependencies:

Reverse depends: clustTool, kappalab, LinearizedSVR, MVpower, pathClass, rminer, rvmbinary, SVMMaj
Reverse imports: pi0, plsRcox, Synth
Reverse suggests: apcluster, caret, colorspace, dismo, evtree, modelcf, plsRcox, pmml, rattle, SPOT, vcd
Reverse enhances: clue