Classification and Visualization
Barycentric plots
Calculation of beta scaling parameters
Benchmarking on B3 data
Scale membership values according to a beta scaling
Calculation of transition probabilities
Lines from classborders to the center
Classification scatterplot matrix
Calculation of Condition Indices for Linear Regression
Function to identify groups of highly correlated variables for removin...
Extracts variable cluster IDs
Internal function to convert a distance structure to a matrix
Estimate density of a given kernel
Density of a Multivariate Normal Distribution
Plotting the 2-d partitions of classification methods
Function to calculate e- or softmax scaled membership values
Computation of an Eight Direction Arranged Map
Tabulation of prediction errors by classes
Friedman's classification benchmark data
Stepwise forward variable selection for classification
Calculation of HMM Sum of Path
K-Modes Clustering
Localized Linear Discriminant Analysis (LocLDA)
Pairwise variable selection for classification in local models
Minimal Error Classification
Naive Bayes Classifier
Nearest Mean Classification
Plotting the 2-d partitions of classification methods
Plotting marginal posterior class probabilities
Naive Bayes Plot
Plot information values
Localized Linear Discriminant Analysis (LocLDA)
predict method for locpvs objects
Prediction of Minimal Error Classification
Naive Bayes Classifier
predict method for pvs objects
Regularized Discriminant Analysis (RDA)
Simple k Nearest Neighbours Classification
Interface to SVMlight
Weights of evidence
Pairwise variable selection for classification
Plotting of 4 dimensional membership representation simplex
Transforming of 4 dimensional values in a barycentric coordinate syste...
Regularized Discriminant Analysis (RDA)
Linear transformation of data
Plotting Eight Direction Arranged Maps or Self-Organizing Maps
Simple k nearest Neighbours
Stepwise variable selection for classification
Interface to SVMlight
Computation of criterion S of a visualization
Barycentric plots
Barycentric plots
Barycentric plots
Barycentric plots
Barycentric plots
Uschi's classification performance measures
Weights of evidence
Variable clustering based variable selection
Miscellaneous functions for classification and visualization, e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes, an interface to 'svmlight' and stepclass() wrapper variable selection for supervised classification, partimat() visualization of classification rules and shardsplot() of cluster results as well as kmodes() clustering for categorical data, corclust() variable clustering, variable extraction from different variable clustering models and weight of evidence preprocessing.