PPtreeregViz (version 2.0.5)

predict.PPTreereg: predict PPTreereg

Description

predict projection pursuit regression tree

Usage

# S3 method for PPTreereg
predict(
  object,
  newdata = NULL,
  Rule = 1,
  final.rule = 1,
  classinfo = FALSE,
  ...
)

Value

Numeric

Arguments

object

a fitted object of class inheriting from PPTreereg

newdata

the test data set

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 group size 9: cutoff that minimize error rates in each node

final.rule

final rule to assign numerical values in the final nodes. 1: mean value in the final nodes 2: median value in the final nodes 3: using optimal projection 4: using all independent variables 5: using several significant independent variables

classinfo

return final node information. Default value is FALSE

...

arguments to be passed to methods

Details

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

Examples

data(dataXY)
Model <- PPTreereg(Y~., data = dataXY, DEPTH = 2)
predict(Model)