klaR v0.6-8

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by Uwe Ligges

Classification and visualization

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

Functions in klaR

Name Description
greedy.wilks Stepwise forward variable selection for classification
predict.rda Regularized Discriminant Analysis (RDA)
plot.NaiveBayes Naive Bayes Plot
kmodes K-Modes Clustering
betascale Scale membership values according to a beta scaling
meclight.default Minimal Error Classification
trigrid Barycentric plots
rda Regularized Discriminant Analysis (RDA)
NaiveBayes Naive Bayes Classifier
predict.NaiveBayes Naive Bayes Classifier
ucpm Uschi's classification performance measures
drawparti Plotting the 2-d partitions of classification methods
dkernel Estimate density of a given kernel
centerlines Lines from classborders to the center
predict.loclda Localized Linear Discriminant Analysis (LocLDA)
.dmvnorm Density of a Multivariate Normal Distribution
distmirr Internal function to convert a distance structure to a matrix
EDAM Computation of an Eight Direction Arranged Map
errormatrix Tabulation of prediction errors by classes
pvs Pairwise variable selection for classification
nm Nearest Mean Classification
TopoS Computation of criterion S of a visualization
predict.svmlight Interface to SVMlight
b.scal Calculation of beta scaling parameters
friedman.data Friedman's classification benchmark data
quadtrafo Transforming of 4 dimensional values in a barycentric coordinate system.
calc.trans Calculation of transition probabilities
predict.locpvs predict method for locpvs objects
predict.pvs predict method for pvs objects
triplot Barycentric plots
tritrafo Barycentric plots
predict.meclight Prediction of Minimal Error Classification
classscatter Classification scatterplot matrix
shardsplot Plotting Eight Direction Arranged Maps or Self-Organizing Maps
svmlight Interface to SVMlight
corclust Function to identify groups of highly correlated variables for removing correlated features from the data for further analysis.
triframe Barycentric plots
stepclass Stepwise variable selection for classification
e.scal Function to calculate e- or softmax scaled membership values
quadplot Plotting of 4 dimensional membership representation simplex
benchB3 Benchmarking on B3 data
partimat Plotting the 2-d partitions of classification methods
hmm.sop Calculation of HMM Sum of Path
predict.sknn Simple k Nearest Neighbours Classification
rerange Linear transformation of data
countries Socioeconomic data for the most populous countries.
plineplot Plotting marginal posterior class probabilities
sknn Simple k nearest Neighbours
triperplines Barycentric plots
B3 West German Business Cycles 1955-1994
loclda Localized Linear Discriminant Analysis (LocLDA)
locpvs Pairwise variable selection for classification in local models
tripoints Barycentric plots
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Details

Date 2013-03-27
SystemRequirements SVMlight
License GPL-2
URL http://www.statistik.tu-dortmund.de
Packaged 2013-03-27 19:39:04 UTC; ligges
NeedsCompilation no
Repository CRAN
Date/Publication 2013-03-27 20:56:39

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