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klaR (version 0.6-11)
Classification and visualization
Description
Miscellaneous functions for classification and visualization developed at the Fakultaet Statistik, Technische Universitaet Dortmund
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Install
install.packages('klaR')
Monthly Downloads
12,093
Version
0.6-11
License
GPL-2
Maintainer
Uwe Ligges
Last Published
June 10th, 2014
Functions in klaR (0.6-11)
Search all functions
distmirr
Internal function to convert a distance structure to a matrix
drawparti
Plotting the 2-d partitions of classification methods
betascale
Scale membership values according to a beta scaling
.dmvnorm
Density of a Multivariate Normal Distribution
predict.pvs
predict method for pvs objects
e.scal
Function to calculate e- or softmax scaled membership values
partimat
Plotting the 2-d partitions of classification methods
plineplot
Plotting marginal posterior class probabilities
NaiveBayes
Naive Bayes Classifier
quadplot
Plotting of 4 dimensional membership representation simplex
predict.rda
Regularized Discriminant Analysis (RDA)
predict.svmlight
Interface to SVMlight
classscatter
Classification scatterplot matrix
errormatrix
Tabulation of prediction errors by classes
EDAM
Computation of an Eight Direction Arranged Map
nm
Nearest Mean Classification
stepclass
Stepwise variable selection for classification
triperplines
Barycentric plots
countries
Socioeconomic data for the most populous countries.
predict.sknn
Simple k Nearest Neighbours Classification
trigrid
Barycentric plots
meclight.default
Minimal Error Classification
plot.NaiveBayes
Naive Bayes Plot
corclust
Function to identify groups of highly correlated variables for removing correlated features from the data for further analysis.
GermanCredit
Statlog German Credit
TopoS
Computation of criterion S of a visualization
calc.trans
Calculation of transition probabilities
plot.woe
Plot information values
B3
West German Business Cycles 1955-1994
predict.NaiveBayes
Naive Bayes Classifier
svmlight
Interface to SVMlight
sknn
Simple k nearest Neighbours
tritrafo
Barycentric plots
locpvs
Pairwise variable selection for classification in local models
centerlines
Lines from classborders to the center
triplot
Barycentric plots
loclda
Localized Linear Discriminant Analysis (LocLDA)
pvs
Pairwise variable selection for classification
ucpm
Uschi's classification performance measures
tripoints
Barycentric plots
woe
Weights of evidence
kmodes
K-Modes Clustering
dkernel
Estimate density of a given kernel
benchB3
Benchmarking on B3 data
triframe
Barycentric plots
friedman.data
Friedman's classification benchmark data
hmm.sop
Calculation of HMM Sum of Path
rerange
Linear transformation of data
predict.meclight
Prediction of Minimal Error Classification
b.scal
Calculation of beta scaling parameters
quadtrafo
Transforming of 4 dimensional values in a barycentric coordinate system.
shardsplot
Plotting Eight Direction Arranged Maps or Self-Organizing Maps
greedy.wilks
Stepwise forward variable selection for classification
predict.woe
Weights of evidence
rda
Regularized Discriminant Analysis (RDA)
predict.loclda
Localized Linear Discriminant Analysis (LocLDA)
predict.locpvs
predict method for locpvs objects