LDA.Tree: Find PP tree structure using LDA

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/LDATree.R

Description

Find tree structure using linear discriminant in each split.

Usage

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

Arguments

i.data

A training data without class information

i.class

class information

weight

weight flag using in LDA 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

1
2
3
4
5
6
7
8
9
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 <- LDA.Tree(iris[train,5],iris[train,1:4])
Tree.result

PPtree documentation built on May 29, 2017, 5:48 p.m.

Search within the PPtree package
Search all R packages, documentation and source code