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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 |
| Reference manual: | klaR.pdf |
| Package source: | klaR_1.7-3.tar.gz |
| Windows binaries: | r-devel: klaR_1.7-3.zip, r-release: klaR_1.7-3.zip, r-oldrel: klaR_1.7-3.zip |
| macOS binaries: | r-release (arm64): klaR_1.7-3.tgz, r-oldrel (arm64): klaR_1.7-3.tgz, r-release (x86_64): klaR_1.7-3.tgz, r-oldrel (x86_64): klaR_1.7-3.tgz |
| Old sources: | klaR archive |
| Reverse imports: | CLUSTShiny, DA, diceR, ezECM, fingerPro, FPDclustering, multilevLCA, pheble, SVMDO |
| Reverse suggests: | assignPOP, butcher, caret, caretEnsemble, discrim, finetune, flowml, fscaret, hda, MLInterfaces, mlr, telescope, tidyAML, tidyclust, TunePareto |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.