klaR v0.6-1

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

Date 2009-11-16
SystemRequirements SVMlight
License GPL-2
URL http://www.statistik.tu-dortmund.de
Packaged 2009-11-16 16:02:35 UTC; ligges
Repository CRAN
Date/Publication 2009-11-16 19:25:17

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