Miscellaneous functions for classification and visualization, e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes, an interface to 'svmlight' and stepclass() wrapper variable selection for supervised classification, partimat() visualization of classification rules and shardsplot() of cluster results as well as kmodes() clustering for categorical data, corclust() variable clustering, variable extraction from different variable clustering models and weight of evidence preprocessing.
Version: 1.7-3 Depends: R (≥ 2.10.0), MASS Imports: combinat, questionr, grDevices, stats, utils, graphics Suggests: scatterplot3d (≥ 0.3-22), som, mlbench, rpart, e1071 Enhances: clustMixType, randomForest, ClustVarLV Published: 2023-12-13 DOI: 10.32614/CRAN.package.klaR Author: Christian Roever, Nils Raabe, Karsten Luebke, Uwe Ligges, Gero Szepannek, Marc Zentgraf, David Meyer Maintainer: Uwe Ligges <ligges at statistik.tu-dortmund.de> License: GPL-2 | GPL-3 URL: https://statistik.tu-dortmund.de NeedsCompilation: no SystemRequirements: SVMlight Citation: klaR citation info Materials: NEWS In views: MachineLearning CRAN checks: klaR results Documentation: Downloads: Reverse dependencies: Reverse depends: LogisticEnsembles Reverse imports: CLUSTShiny, DA, diceR, ezECM, fingerPro, FPDclustering, multilevLCA, SVMDO, VICatMix Reverse suggests: assignPOP, butcher, caret, caretEnsemble, discrim, fastml, finetune, flowml, hda, MLInterfaces, mlr, pathMED, telescope, tidyAML, tidyclust, TunePareto Linking:Please use the canonical form https://CRAN.R-project.org/package=klaR to link to this page.
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