PP.Tree {classPP}R Documentation

Find PP tree structure

Description

Find tree structure using projection pursuit in each split.

Usage

PP.Tree(PPmethod, i.class, i.data, weight = TRUE, r=NULL,lambda=NULL) 

Arguments

PPmethod Selected PP index
``LDA" - LDA index
``Lp" - Lp index;
``PDA" - PDA index
i.data A training data without class information
i.class class information
weight weight flag using in LDA index
r a parameter for L_r index
lambda a parameter for PDA index

Value

Tree.Struct Tree structure
Alpha.Keep 1D projection of each split
C.Keep spliting rule for each split

Author(s)

Eun-kyung Lee

References

Lee, E., Cook, D., and Klinke, S.(2002) Projection Pursuit indices for supervised classification

See Also

{PPindex.class}, {PP.optimize}

Examples


data(iris)
n <- nrow(iris)
tot <- c(1:n)
n.train <- round(n*0.9)
train <- sample(tot,n.train)
test <- tot[-train]

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

[Package classPP version 1.0.2 Index]