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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: 0.9-33
Depends: R (≥ 2.10)
Imports: methods, stats, grDevices, graphics
Published: 2024-08-13
DOI: 10.32614/CRAN.package.kernlab
Author: Alexandros Karatzoglou [aut, cre], Alex Smola [aut], Kurt Hornik ORCID iD [aut], National ICT Australia (NICTA) [cph], Michael A. Maniscalco [ctb, cph], Choon Hui Teo [ctb]
Maintainer: Alexandros Karatzoglou <alexandros.karatzoglou at gmail.com>
License: GPL-2
Copyright: see file COPYRIGHTS
NeedsCompilation: yes
Citation: kernlab citation info
In views: Cluster, MachineLearning, NaturalLanguageProcessing, Optimization
CRAN checks: kernlab results

Documentation:

Reference manual: kernlab.pdf
Vignettes: kernlab - An S4 Package for Kernel Methods in R (source, R code)

Downloads:

Package source: kernlab_0.9-33.tar.gz
Windows binaries: r-devel: kernlab_0.9-33.zip, r-release: kernlab_0.9-33.zip, r-oldrel: kernlab_0.9-33.zip
macOS binaries: r-release (arm64): kernlab_0.9-33.tgz, r-oldrel (arm64): kernlab_0.9-33.tgz, r-release (x86_64): kernlab_0.9-33.tgz, r-oldrel (x86_64): kernlab_0.9-33.tgz
Old sources: kernlab archive

Reverse dependencies:

Reverse depends: CVST, DRR, DTRlearn2, Iscores, kappalab, kebabs, kfda, KPC, omada, PPInfer, svmpath
Reverse imports: ABPS, ADImpute, ampir, AnimalSequences, aweSOM, bootcluster, BPRMeth, brainKCCA, branchpointer, calibrateBinary, classmap, clusterExperiment, CondIndTests, CondiS, DA, DMTL, DynTxRegime, Ecume, ehymet, finnts, flevr, fmf, fpc, fPortfolio, gecko, GeneGeneInteR, GeneralisedCovarianceMeasure, geomod, ggscidca, gkmSVM, GreedyExperimentalDesign, kernelFactory, kerntools, KnowSeq, kpcaIG, kpcalg, KRMM, ks, lsirm12pl, MachineShop, microsynth, mikropml, mildsvm, mixtools, nlcv, oddstream, OmicSense, PCDimension, personalized, pheble, PIUMA, PLORN, plsRcox, PredCRG, pRoloc, promor, qrjoint, QuESTr, randomMachines, REMP, RISCA, Rmagpie, rminer, robCompositions, ROI.plugin.ipop, rres, RSSL, scAnnotatR, scPCA, scRecover, ssMutPA, STGS, survivalsvm, SVMMaj, Synth, tboot, TDApplied, tidysynth, tsensembler, TSGS, tsiR, visaOTR, wearables
Reverse suggests: aum, BiodiversityR, breakDown, bundle, butcher, caret, colorspace, CompareCausalNetworks, condvis2, dials, diceR, dimRed, dismo, evclust, evtree, fastml, FCPS, flowml, fscaret, gamclass, GAparsimony, healthyR.ts, HPiP, iForecast, isotree, loon, mistral, mistyR, MLInterfaces, mlr, mlr3cluster, mlr3pipelines, mlrMBO, MLSeq, modeltime, MSCMT, parsnip, pdp, pmml, rattle, recipes, RStoolbox, sand, Semblance, shipunov, soilassessment, spectralGraphTopology, ssc, SSLR, stacks, SuperLearner, superMICE, supervisedPRIM, swag, tidyAML, tidysdm, tune, vcd, viralmodels, WeightSVM
Reverse enhances: clue, prediction

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.