PPclassify {PPtreeViz} | R Documentation |
predict projection pursuit classification tree
PPclassify(Tree.result,test.data,Rule,true.class=NULL,...)
Tree.result |
PPtreeclass object |
test.data |
the test dataset |
Rule |
split rule 1: mean of two group means 2: weighted mean of two group means - weight with group size 3: weighted mean of two group means - weight with group sd 4: weighted mean of two group means - weight with group se 5: mean of two group medians 6: weighted mean of two group medians - weight with group size 7: weighted mean of two group median - weight with group IQR 8: weighted mean of two group median - weight with group IQR and size |
true.class |
true class of test dataset if available |
... |
arguments to be passed to methods |
Predict class for the test set with the fitted projection pursuit classification tree and calculate prediction error.
predict.class predicted class
predict.error number of the prediction errors
Lee, YD, Cook, D., Park JW, and Lee, EK(2013) PPtree: Projection Pursuit Classification Tree, Electronic Journal of Statistics, 7:1369-1386.
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 <- PPTreeclass(Species~.,data=iris[train,],"LDA")
PPclassify(Tree.result,iris[test,1:4],1,iris[test,5])