kernlab: Kernel-Based Machine Learning Lab (original) (raw)

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, AnimalSequences, aweSOM, bootcluster, BPRMeth, brainKCCA, branchpointer, calibrateBinary, CIDER, 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, 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, S4DM, scAnnotatR, scPCA, scRecover, ssMutPA, survivalsvm, SVMMaj, Synth, tboot, TDApplied, tidysynth, tsensembler, TSGS, tsiR, visaOTR, wearables

Reverse suggests:

aum, BiodiversityR, breakDown, bundle, butcher, caret, colorspace, CompareCausalNetworks, condvis2, DataSimilarity, dials, diceR, dimRed, dismo, evclust, evtree, fastml, FCPS, flowml, fscaret, gamclass, GAparsimony, healthyR.ts, HPiP, iForecast, isotree, LLMAgentR, loon, mistral, mistyR, MLInterfaces, mlr, mlr3cluster, mlr3pipelines, mlrMBO, MLSeq, modeltime, MSCMT, parsnip, pathMED, pdp, pmml, rattle, recipes, RStoolbox, sand, Semblance, shipunov, soilassessment, spect, ssc, SSLR, stacks, SuperLearner, superMICE, supervisedPRIM, swag, tidyAML, tidysdm, tune, vcd, viralmodels, WeightSVM

Reverse enhances:

clue, prediction