View source: R/PPTreeclass_MOD.R
PPTreeclass_MOD | R Documentation |
Construct the projection pursuit classification tree MOD
PPTreeclass_MOD(formula,data, PPmethod="LDA",weight=TRUE, r=1,lambda=0.1,energy=0,maxiter=50000,strule = 1,tot,...)
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 |
strule |
select the stoping rule rule based in G=1 pure node |
tot |
total obs original class |
... |
arguments to be passed to methods |
Find tree structure using various projection pursuit indices of classification in each split.
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
Lee, YD, Cook, D., Park JW, and Lee, EK(2013) PPtree: Projection Pursuit Classification Tree, Electronic Journal of Statistics, 7:1369-1386.
data(iris) Tree.result <- PPTreeclass_MOD(Species~.,data = iris,"LDA") Tree.result
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.