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: |
0.9-29 |
| Depends: |
R (≥ 2.10) |
| Imports: |
methods, stats, grDevices, graphics |
| Published: |
2019-11-12 |
| Author: |
Alexandros Karatzoglou [aut, cre],
Alex Smola [aut],
Kurt Hornik [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 |
| SystemRequirements: |
C++11 |
| Citation: |
kernlab citation info |
| In views: |
Cluster, MachineLearning, Multivariate, NaturalLanguageProcessing, Optimization |
| CRAN checks: |
kernlab results |
| Reverse depends: |
CVST, DRR, DTRlearn2, kappalab, kfda, probsvm, RaPKod, svmadmm |
| Reverse imports: |
ABPS, ampir, BKPC, brainKCCA, calibrateBinary, CondIndTests, DeLorean, diceR, DynTxRegime, fpc, fPortfolio, funcy, GeneralisedCovarianceMeasure, gkmSVM, ITRLearn, kernelFactory, kernelPSI, kpcalg, KRMM, ks, MachineShop, microsynth, MTGS, nlcv, oddstream, PCDimension, personalized, plsRcox, qrjoint, qrsvm, RiemBaseExt, rminer, RMKL, robCompositions, rres, RSSL, soilassessment, STGS, survivalsvm, SVMMaj, SwarmSVM, Synth, tsiR, VRPM |
| Reverse suggests: |
BiodiversityR, breakDown, butcher, caret, caretEnsemble, colorspace, CompareCausalNetworks, condvis2, dials, dimRed, dismo, evtree, FactorsR, fscaret, GAparsimony, kernelTDA, loon, mistral, mlr, mlr3pipelines, mlrMBO, MSCMT, parsnip, pdp, pmml, preprocomb, rattle, recipes, RStoolbox, sand, Semblance, shipunov, spectralGraphTopology, ssc, SuperLearner, supervisedPRIM, vcd |
| Reverse enhances: |
clue, prediction |