parse_party {TSDT} | R Documentation |
parse_party
Description
Parse output from ctree() and mob() functions in party package.
Usage
parse_party(tree, data = NULL, include_subgroups = FALSE, digits = NULL)
Arguments
tree |
An object of class BinaryTree or mob resulting from a call to the ctree() or mob() function. |
data |
data.frame containing covariates used to create tree. |
include_subgroups |
A logical value indicating whether or not to include a string representation of the subgroups in the results. Defaults to FALSE. |
digits |
Number of digits for rounding. |
Details
Collects text output from party::ctree() or party::mob(), parses the splits, and populates a data.frame with the relevant data.
Value
A data.frame containing a parsed tree.
See Also
Examples
requireNamespace( "party", quietly = TRUE )
requireNamespace( "modeltools", quietly = TRUE )
## From party::ctree() examples:
set.seed(290875)
## regression
airq <- subset(airquality, !is.na(Ozone))
airct <- party::ctree(Ozone ~ ., data = airq,
controls = party::ctree_control(maxsurrogate = 3))
## Parse the results into a new data.frame
ex1 <- parse_party( airct )
ex1
## From party::mob() examples:
data("BostonHousing", package = "mlbench")
## and transform variables appropriately (for a linear regression)
BostonHousing$lstat <- log(BostonHousing$lstat)
BostonHousing$rm <- BostonHousing$rm^2
## as well as partitioning variables (for fluctuation testing)
BostonHousing$chas <- factor( BostonHousing$chas, levels = 0:1,
labels = c("no", "yes") )
BostonHousing$rad <- factor(BostonHousing$rad, ordered = TRUE)
## partition the linear regression model medv ~ lstat + rm
## with respect to all remaining variables:
fmBH <- party::mob( medv ~ lstat + rm | zn + indus + chas + nox + age +
dis + rad + tax + crim + b + ptratio,
control = party::mob_control(minsplit = 40), data = BostonHousing,
model = modeltools::linearModel )
## Parse the results into a new data.frame
ex2 <- parse_party( fmBH )
ex2
[Package TSDT version 1.0.7 Index]