PPclassify_MOD: predict PPtree

In natydasilva/PPtreeExt: Projection Pursuit Classification Tree extensions

predict PPtree

Description

Predict class for the test set with the fitted projection pursuit classification tree and calculate prediction error.

Usage

PPclassify_MOD(Tree.result,test.data,true.class=NULL,...)

Arguments

Tree.result	PPtreeclass object
test.data	the test dataset
true.class	true class of test dataset if available
...	arguments to be passed to methods

Value

predict.class predicted class

predict.error number of the prediction errors

References

Lee, YD, Cook, D., Park JW, and Lee, EK(2013) PPtree: Projection Pursuit Classification Tree, Electronic Journal of Statistics, 7:1369-1386.

Examples

data(penguins)
penguins <- na.omit(penguins[, -c(2,7, 8)])
require(rsample)
penguins_spl <- rsample::initial_split(penguins, strata=species)
penguins_train <- training(penguins_spl)
penguins_test <- testing(penguins_spl)
penguins_ppt <- PPTreeclass_MOD(species~bill_len + bill_dep +
  flipper_len + body_mass, data = penguins_train, PPmethod = "LDA")
PPclassify_MOD(penguins_ppt, test.data=penguins_test[,-1], true.class = penguins_test$species)

natydasilva/PPtreeExt documentation built on June 14, 2025, 12:18 p.m.