Classification and Visualization

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. |

cvtree | Extracts variable cluster IDs |

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 |

xtractvars | Variable clustering based variable selection |

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