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, DTRlearn2, Iscores, kappalab, kebabs, kfda, KPC, omada, PPInfer, svmpath |
| Reverse imports: |
ABPS, ADImpute, ampir, aweSOM, BPRMeth, brainKCCA, branchpointer, calibrateBinary, classmap, clusterExperiment, CondIndTests, CondiS, DA, DMTL, DynTxRegime, Ecume, finnts, flevr, fmf, fpc, fPortfolio, gecko, GeneGeneInteR, GeneralisedCovarianceMeasure, geomod, gkmSVM, GreedyExperimentalDesign, kernelFactory, KnowSeq, 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, Synth, tboot, TDApplied, tidysynth, tsensembler, TSGS, tsiR, visaOTR, wearables |
| Reverse suggests: |
aum, BiodiversityR, breakDown, bundle, butcher, caret, caretEnsemble, colorspace, CompareCausalNetworks, condvis2, dials, diceR, dimRed, dismo, evclust, evtree, FCPS, flowml, fscaret, gamclass, GAparsimony, HPiP, iForecast, isotree, LDLcalc, loon, MACP, microbiomeMarker, 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, WeightSVM |
| Reverse enhances: |
clue, prediction |
[aut],
National ICT Australia (NICTA) [cph],
Michael A. Maniscalco [ctb, cph],
Choon Hui Teo [ctb]