PPtreeViz (version 2.0.4)

PPTreeclass: Projection pursuit classification tree

Description

Construct the projection pursuit classification tree

Usage

PPTreeclass(formula,data, PPmethod="LDA",weight=TRUE,
                     r=1,lambda=0.1,energy=0,maxiter=50000,...)

Arguments

formula

an object of class "formula"

data

data frame

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

parameter for the probability to take new projection

maxiter

maximum iteration number

...

arguments to be passed to methods

Value

Tree.Struct tree structure of projection pursuit classification tree

projbest.node 1 dimensional optimal projections of each node split

splitCutoff.node cutoff values of each node split

origclass original class

origdata original data

Details

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

References

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

Examples

# NOT RUN {
data(iris)
Tree.result <- PPTreeclass(Species~.,data = iris,"LDA")
Tree.result
# }