klaR: Classification and visualization

Miscellaneous functions for classification and visualization developed at the Fakultaet Statistik, Technische Universitaet Dortmund, 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.

AuthorChristian Roever, Nils Raabe, Karsten Luebke, Uwe Ligges, Gero Szepannek, Marc Zentgraf
Date of publication2016-07-18 15:02:59
MaintainerUwe Ligges <ligges@statistik.tu-dortmund.de>
LicenseGPL-2
Version0.6-12
http://www.statistik.tu-dortmund.de

View on R-Forge

Man pages

B3: West German Business Cycles 1955-1994

benchB3: Benchmarking on B3 data

betascale: Scale membership values according to a beta scaling

b.scal: Calculation of beta scaling parameters

calc.trans: Calculation of transition probabilities

centerlines: Lines from classborders to the center

classscatter: Classification scatterplot matrix

cond.index: Calculation of Condition Indices for Linear Regression

corclust: Function to identify groups of highly correlated variables...

countries: Socioeconomic data for the most populous countries.

distmirr: Internal function to convert a distance structure to a matrix

dkernel: Estimate density of a given kernel

dmvnorm: Density of a Multivariate Normal Distribution

drawparti: Plotting the 2-d partitions of classification methods

EDAM: Computation of an Eight Direction Arranged Map

errormatrix: Tabulation of prediction errors by classes

e.scal: Function to calculate e- or softmax scaled membership values

friedmandata: Friedman's classification benchmark data

GermanCredit: Statlog German Credit

greedy.wilks: Stepwise forward variable selection for classification

hmm.sop: Calculation of HMM Sum of Path

kmodes: K-Modes Clustering

loclda: Localized Linear Discriminant Analysis (LocLDA)

locpvs: Pairwise variable selection for classification in local...

meclight: Minimal Error Classification

NaiveBayes: Naive Bayes Classifier

nm: Nearest Mean Classification

partimat: Plotting the 2-d partitions of classification methods

plineplot: Plotting marginal posterior class probabilities

plot.NaiveBayes: Naive Bayes Plot

plot.woe: Plot information values

predict.loclda: Localized Linear Discriminant Analysis (LocLDA)

predict.locpvs: predict method for locpvs objects

predict.meclight: Prediction of Minimal Error Classification

predict.NaiveBayes: Naive Bayes Classifier

predict.pvs: predict method for pvs objects

predict.rda: Regularized Discriminant Analysis (RDA)

predict.sknn: Simple k Nearest Neighbours Classification

predict.svmlight: Interface to SVMlight

predict.woe: Weights of evidence

pvs: Pairwise variable selection for classification

quadplot: Plotting of 4 dimensional membership representation simplex

quadtrafo: Transforming of 4 dimensional values in a barycentric...

rda: Regularized Discriminant Analysis (RDA)

rerange: Linear transformation of data

shardsplot: Plotting Eight Direction Arranged Maps or Self-Organizing...

sknn: Simple k nearest Neighbours

stepclass: Stepwise variable selection for classification

svmlight: Interface to SVMlight

TopoS: Computation of criterion S of a visualization

triframe: Barycentric plots

trigrid: Barycentric plots

triperplines: Barycentric plots

triplot: Barycentric plots

tripoints: Barycentric plots

tritrafo: Barycentric plots

ucpm: Uschi's classification performance measures

woe: Weights of evidence

Files in this package

klaR/DESCRIPTION
klaR/NAMESPACE
klaR/NEWS
klaR/R
klaR/R/EDAM.R klaR/R/NaiveBayes.R klaR/R/TopoS.R klaR/R/benchB3.R klaR/R/betaskal.R klaR/R/calc.trans.R klaR/R/centerlines.R klaR/R/classscatter.R klaR/R/cond.index.R klaR/R/corclust.R klaR/R/dkernel.R klaR/R/e.scal.R klaR/R/errormatrix.R klaR/R/friedmandata.R klaR/R/greedy.wilks.R klaR/R/hmm.sop.R klaR/R/kmodes.R klaR/R/level_shardsplot.R klaR/R/loclda.R
klaR/R/locpvs.R
klaR/R/meclight.R klaR/R/membercheck.R klaR/R/nm.R klaR/R/partimat.R klaR/R/plineplot.R klaR/R/plot.NaiveBayes.R klaR/R/plot.edam.R klaR/R/predict.NaiveBayes.R klaR/R/quadplot.R klaR/R/rda.R klaR/R/rerange.R klaR/R/shardsplot.R klaR/R/sknn.R klaR/R/stepclass.R klaR/R/svmlight.R klaR/R/triplot.R klaR/R/ucpm.R klaR/R/woe.R
klaR/data
klaR/data/B3.RData
klaR/data/GermanCredit.RData
klaR/data/countries.RData
klaR/inst
klaR/inst/CITATION
klaR/man
klaR/man/B3.Rd klaR/man/EDAM.Rd klaR/man/GermanCredit.Rd klaR/man/NaiveBayes.Rd klaR/man/TopoS.Rd klaR/man/b.scal.Rd klaR/man/benchB3.Rd klaR/man/betascale.Rd klaR/man/calc.trans.Rd klaR/man/centerlines.Rd klaR/man/classscatter.Rd klaR/man/cond.index.Rd klaR/man/corclust.Rd klaR/man/countries.Rd klaR/man/distmirr.Rd klaR/man/dkernel.Rd klaR/man/dmvnorm.Rd klaR/man/drawparti.Rd klaR/man/e.scal.Rd klaR/man/errormatrix.Rd klaR/man/friedmandata.Rd klaR/man/greedy.wilks.Rd klaR/man/hmm.sop.Rd klaR/man/kmodes.Rd klaR/man/loclda.Rd klaR/man/locpvs.Rd klaR/man/meclight.Rd klaR/man/nm.Rd klaR/man/partimat.Rd klaR/man/plineplot.Rd klaR/man/plot.NaiveBayes.Rd klaR/man/plot.woe.Rd klaR/man/predict.NaiveBayes.Rd klaR/man/predict.loclda.Rd klaR/man/predict.locpvs.Rd klaR/man/predict.meclight.Rd klaR/man/predict.pvs.Rd klaR/man/predict.rda.Rd klaR/man/predict.sknn.Rd klaR/man/predict.svmlight.Rd klaR/man/predict.woe.Rd klaR/man/pvs.Rd klaR/man/quadplot.Rd klaR/man/quadtrafo.Rd klaR/man/rda.Rd klaR/man/rerange.Rd klaR/man/shardsplot.Rd klaR/man/sknn.Rd klaR/man/stepclass.Rd klaR/man/svmlight.Rd klaR/man/triframe.Rd klaR/man/trigrid.Rd klaR/man/triperplines.Rd klaR/man/triplot.Rd klaR/man/tripoints.Rd klaR/man/tritrafo.Rd klaR/man/ucpm.Rd klaR/man/woe.Rd
klaR/tests
klaR/tests/EDAM.R
klaR/tests/EDAM.Rout.save
klaR/tests/EDAM.ps.save
klaR/tests/testklaR.ps.save
klaR/tests/testsklaR.R
klaR/tests/testsklaR.Rout.save

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