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.
| Reverse depends: |
CVST, DRR, kappalab, kfda, KPC, svmpath |
| Reverse imports: |
ABPS, ampir, AnimalSequences, aweSOM, bigPLScox, BKPC, bootcluster, brainKCCA, calibrateBinary, causalweight, CFM, classmap, clusterWebApp, CondiS, DA, DTRlearn2, DynTxRegime, Ecume, ehymet, finnts, flevr, fpc, fPortfolio, gecko, geomod, ggscidca, gkmSVM, GreedyExperimentalDesign, Iscores, kernelFactory, kerntools, kpcaIG, KRMM, ks, lsirm12pl, MachineShop, microsynth, mikropml, mildsvm, mixtools, nlcv, oddstream, OmicSense, PCDimension, personalized, PLORN, plsRcox, ProbSVMs, promor, qrjoint, QuESTr, randomMachines, RISCA, rminer, roclab, ROI.plugin.ipop, rres, RSSL, rvmprior, S4DM, ssMutPA, STATassist, survivalsvm, SVMMaj, Synth, T1FF, tboot, TDApplied, tidysynth, tsensembler, TSGS, tsiR |
| Reverse suggests: |
AgriFusionR, aum, BiodiversityR, breakDown, bundle, butcher, caret, colorspace, condvis2, DataSimilarity, dials, diceR, dimRed, dismo, E2E, ensModelVis, EpidigiR, evtree, fastml, FBMS, FCPS, featR, gamclass, GAparsimony, healthyR.ts, iForecast, isotree, LLMAgentR, loon, mistral, mlr, mlr3cluster, mlr3pipelines, mlrMBO, mlS3, mlspatial, MLwrap, modeltime, MSCMT, multiDEGGs, OpEnCAMeO, OpEnCAST, orbital, parsnip, pdp, pmml, rattle, recipes, robCompositions, RStoolbox, sand, soilassessment, spect, SpoMAG, ssc, stacks, SuperLearner, supervisedPRIM, swag, themis, tidyAML, tidypredict, tidysdm, tune, vcd, WeightSVM, writeAlizer |
| Reverse enhances: |
clue, prediction |
[aut],
National ICT Australia (NICTA) [cph],
Michael A. Maniscalco [ctb, cph],
Choon Hui Teo [ctb]