PPtreeViz (version 1.0.3)

PP.Tree.class: Projection pursuit classification tree with various PP indices

Description

Find tree structure using various projection pursuit indices of classification in each split.

Usage

PP.Tree.class(origclass, origdata, PPmethod="LDA",weight=TRUE,r=1,lambda=0.1,
              energy=0,maxiter=50000, ...)

Arguments

origclass

class information vector

origdata

numeric data matrix without class information

PPmethod

method for projection pursuit; "LDA", "PDA", "Lr", "GINI", and "ENTROPY"

weight

weight flag in LDA, PDA and Lr index

r

r in Lr index

lambda

lambda in PDA index

energy

energy parameter

maxiter

number of maximum iteration

...

arguments to be passed to methods

Value

• Tree.Struct Tree structure of projection pursuit classification tree projbest.node 1-dim optimal projections of each split node splitCutoff.node cutoff values of each split node origclass original class origdata original data

References

Lee, YD, Cook, D., Park JW, and Lee, EK(2013) PPtree: Projection pursuit classification tree, Electronic Journal of Statistics, 7:1369-1386.

Examples

data(iris)
Tree.result <- PP.Tree.class(iris[,5],iris[,1:4],"LDA")
Tree.result