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klaR (version 0.6-9)
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
12,565
Version
0.6-9
License
GPL-2
Maintainer
Uwe Ligges
Last Published
July 21st, 2013
Functions in klaR (0.6-9)
Search all functions
betascale
Scale membership values according to a beta scaling
predict.loclda
Localized Linear Discriminant Analysis (LocLDA)
EDAM
Computation of an Eight Direction Arranged Map
greedy.wilks
Stepwise forward variable selection for classification
errormatrix
Tabulation of prediction errors by classes
partimat
Plotting the 2-d partitions of classification methods
b.scal
Calculation of beta scaling parameters
plot.NaiveBayes
Naive Bayes Plot
kmodes
K-Modes Clustering
hmm.sop
Calculation of HMM Sum of Path
locpvs
Pairwise variable selection for classification in local models
ucpm
Uschi's classification performance measures
quadplot
Plotting of 4 dimensional membership representation simplex
tritrafo
Barycentric plots
stepclass
Stepwise variable selection for classification
triplot
Barycentric plots
predict.rda
Regularized Discriminant Analysis (RDA)
quadtrafo
Transforming of 4 dimensional values in a barycentric coordinate system.
classscatter
Classification scatterplot matrix
corclust
Function to identify groups of highly correlated variables for removing correlated features from the data for further analysis.
tripoints
Barycentric plots
B3
West German Business Cycles 1955-1994
benchB3
Benchmarking on B3 data
loclda
Localized Linear Discriminant Analysis (LocLDA)
sknn
Simple k nearest Neighbours
e.scal
Function to calculate e- or softmax scaled membership values
TopoS
Computation of criterion S of a visualization
predict.pvs
predict method for pvs objects
triframe
Barycentric plots
predict.woe
Weights of evidence
NaiveBayes
Naive Bayes Classifier
countries
Socioeconomic data for the most populous countries.
drawparti
Plotting the 2-d partitions of classification methods
shardsplot
Plotting Eight Direction Arranged Maps or Self-Organizing Maps
predict.NaiveBayes
Naive Bayes Classifier
friedman.data
Friedman's classification benchmark data
nm
Nearest Mean Classification
predict.meclight
Prediction of Minimal Error Classification
trigrid
Barycentric plots
plot.woe
Plot information values
predict.locpvs
predict method for locpvs objects
pvs
Pairwise variable selection for classification
triperplines
Barycentric plots
centerlines
Lines from classborders to the center
calc.trans
Calculation of transition probabilities
meclight.default
Minimal Error Classification
plineplot
Plotting marginal posterior class probabilities
rda
Regularized Discriminant Analysis (RDA)
predict.svmlight
Interface to SVMlight
distmirr
Internal function to convert a distance structure to a matrix
predict.sknn
Simple k Nearest Neighbours Classification
woe
Weights of evidence
rerange
Linear transformation of data
.dmvnorm
Density of a Multivariate Normal Distribution
dkernel
Estimate density of a given kernel
svmlight
Interface to SVMlight