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, Gaussian Processes and a QP solver.

Version: 0.9-29
Depends: R (≥ 2.10)
Imports: methods, stats, grDevices, graphics
Published: 2019-11-12
Author: Alexandros Karatzoglou [aut, cre], Alex Smola [aut], Kurt Hornik [aut], National ICT Australia (NICTA) [cph], Michael A. Maniscalco [ctb, cph], Choon Hui Teo [ctb]
Maintainer: Alexandros Karatzoglou <alexandros.karatzoglou at>
License: GPL-2
Copyright: see file COPYRIGHTS
NeedsCompilation: yes
SystemRequirements: C++11
Citation: kernlab citation info
In views: Cluster, MachineLearning, Multivariate, NaturalLanguageProcessing, Optimization
CRAN checks: kernlab results


Reference manual: kernlab.pdf
Vignettes: kernlab - An S4 Package for Kernel Methods in R
Package source: kernlab_0.9-29.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): kernlab_0.9-29.tgz, r-release (x86_64): kernlab_0.9-29.tgz, r-oldrel: kernlab_0.9-29.tgz
Old sources: kernlab archive

Reverse dependencies:

Reverse depends: CVST, DRR, DTRlearn2, kappalab, kebabs, kfda, KPC, PPInfer, svmpath
Reverse imports: ABPS, ADImpute, ampir, aweSOM, BKPC, BPRMeth, brainKCCA, branchpointer, calibrateBinary, classmap, clusterExperiment, CondIndTests, DeLorean, DMTL, DynTxRegime, Ecume, fmf, fpc, fPortfolio, GeneGeneInteR, GeneralisedCovarianceMeasure, gkmSVM, GreedyExperimentalDesign, ITRLearn, kernelFactory, kernelPSI, KnowSeq, kpcalg, KRMM, ks, MachineShop, MetaClean, microsynth, mikropml, mixtools, nlcv, oddstream, PCDimension, personalized, plsRcox, PredCRG, pRoloc, qrjoint, REMP, RISCA, Rmagpie, rminer, robCompositions, ROI.plugin.ipop, rres, RSSL, scClassifR, scPCA, scRecover, sdmApp, soilassessment, STGS, survivalsvm, SVMMaj, SwarmSVM, Synth, tboot, tidysynth, tsensembler, tsiR, wearables
Reverse suggests: BiodiversityR, breakDown, butcher, caret, caretEnsemble, colorspace, CompareCausalNetworks, condvis2, dials, diceR, dimRed, dismo, evclust, evtree, FactorsR, FCPS, fscaret, gamclass, GAparsimony, iForecast, landmap, loon, mistral, MLInterfaces, mlr, mlr3cluster, mlr3pipelines, mlrMBO, modeltime, MSCMT, parsnip, pdp, pmml, rattle, recipes, RStoolbox, sand, Semblance, shipunov, spectralGraphTopology, ssc, SSLR, stacks, SuperLearner, supervisedPRIM, swag, tune, vcd
Reverse enhances: clue, prediction


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