PPtreeViz (version 2.0.3)

LDAopt: PP optimization using LDA index

Description

PP optimization using LDA index

Usage

LDAopt(origclass,origdata,q=1,weight=TRUE,...)

Arguments

origclass

class information vector of data

origdata

data matrix without class information

q

dimension of projection vector

weight

weight flag in LDA index

...

arguments to be passed to methods

Value

indexbest maximum LDA index value

projbest optimal q-dimensional projection matrix

origclass original class information vector

origdata original data matrix without class information

Details

Find the q-dimensional optimal projection using LDA projectin pursuit index

References

Lee, EK., Cook, D., Klinke, S., and Lumley, T.(2005) Projection Pursuit for Exploratory Supervised Classification, Journal of Computational and Graphical Statistics, 14(4):831-846.

Examples

# NOT RUN {
data(iris)
LDA.proj.result <- LDAopt(iris[,5],iris[,1:4])
LDA.proj.result$indexbest
LDA.proj.result$projbest
# }