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, DTRlearn, DTRlearn2, exprso, kappalab, kfda, probsvm, RaPKod, svmadmm |
| Reverse imports: |
ABPS, BKPC, brainKCCA, calibrateBinary, CondIndTests, DeLorean, diceR, DynTxRegime, fpc, fPortfolio, gkmSVM, ITRLearn, kernelFactory, kpcalg, KRMM, ks, MachineShop, microsynth, nlcv, PCDimension, personalized, plsRcox, qrjoint, qrsvm, rminer, robCompositions, ROI.plugin.ipop, rres, RSSL, survivalsvm, SVMMaj, SwarmSVM, Synth, tsensembler, tsiR, VRPM |
| Reverse suggests: |
BiodiversityR, breakDown, bWGR, caret, caretEnsemble, colorspace, CompareCausalNetworks, dials, dimRed, dismo, evtree, FactorsR, fscaret, gamclass, GAparsimony, loon, mistral, mlr, mlrMBO, MSCMT, pdp, pmml, preprocomb, rattle, recipes, RStoolbox, sand, Semblance, ssc, SuperLearner, supervisedPRIM, vcd |
| Reverse enhances: |
clue, prediction |