kernlab (0.9-15)

Kernel-based Machine Learning Lab.

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.

Maintainer: Alexandros Karatzoglou
Author(s): Alexandros Karatzoglou, Alex Smola, Kurt Hornik

License: GPL-2

Uses: Does not use any package
Reverse depends: bmrm, clustTool, CVST, DRR, DTRlearn, DTRlearn2, exprso, gene2pathway, kappalab, kfda, LinearizedSVR, MVpower, netClass, pathClass, probsvm, RaPKod, rminer, rvmbinary, stringkernels, svmadmm, SVMMaj, Synth, TreeRank
Reverse suggests: apcluster, BiodiversityR, breakDown, bWGR, caret, caretEnsemble, colorspace, CompareCausalNetworks, conformal, dials, dimRed, dismo, evtree, FactorsR, fpc, fscaret, gamclass, GAparsimony, ks, loon, mistral, mlr, mlrMBO, modelcf, MSCMT, pdp, pi0, plsRcox, pmml, preprocomb, rattle, recipes, RStoolbox, sand, Semblance, SemiSupervised, SPOT, ssc, SuperLearner, supervisedPRIM, TDMR, vcd
Reverse enhances: clue, prediction

Released about 6 years ago.