PDA.Tree: Find PP tree structure using PDA

In PPtree: Projection pursuit classification tree

Description

Find tree structure using projection pursuit in each split.

Usage

PDA.Tree(i.class, i.data, weight = TRUE, lambda=1, ...) 

Arguments

i.data	A training data without class information
i.class	class information
weight	weight flag using in LDA 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 <- PDA.Tree(iris[train,5],iris[train,1:4])
Tree.result

PPtree documentation built on May 2, 2019, 4:22 a.m.