CART: Creates a classification or regression tree.

In Displayr/flipTrees: Tools for classification and regression trees

Creates a classification or regression tree.

Description

Creates a classification or regression tree.

Usage

CART(
  formula,
  data = NULL,
  subset = NULL,
  weights = NULL,
  output = "Sankey",
  missing = "Use partial data",
  prune = "None",
  early.stopping = TRUE,
  auxiliary.data = NULL,
  show.labels = FALSE,
  predictor.level.treatment = "Abbreviated labels",
  outcome.level.treatment = "Full labels",
  decimals = NULL,
  long.running.calculations = TRUE,
  seed = 12321,
  ...
)

Arguments

formula	A formula expression. The left-hand-side (response) should be either a numerical vector when a regression tree will be fitted or a factor, when a classification tree is produced. The right-hand-side should be a series of numeric or factor variables separated by +; there should be no interaction terms. Both . and - are allowed: regression trees can have offset terms
data	A data frame in which to preferentially interpret formula, weights and subset
subset	An optional vector specifying a subset of observations to be used in the fitting process or the name of a variable in data. It may not be an expression.
weights	An optional vector of sampling weights or the name of a variable in data. It may not be an expression.
output	How the tree is represented: "Sankey", "Tree", "Text", "Prediction-Accuracy Table", "Cross Validation" or "Decision Rules"
missing	How missing data is to be treated in the regression. Options are: "Error if missing data", "Exclude cases with missing data", "Use partial data",and "Imputation (replace missing values with estimates)".
prune	How to prune the tree according to the cross-validated error. Options are: "None", "Minimum error" and "Smallest tree".
early.stopping	Whether or not to stop building the tree early if splits are not decreasing the lack of fit sufficiently.
auxiliary.data	A data frame containing additional variables to be used in imputation.
show.labels	Shows the variable labels, as opposed to the names, in the outputs, where a variables label is an attribute (e.g., attr(foo, "label")).
predictor.level.treatment	How predictor factor labels are displayed: "Letters", "Abbreviated labels" or "Full labels".
outcome.level.treatment	How outcome factor labels are displayed: "Letters", "Abbreviated labels" or "Full labels".
decimals	The number of decimal places to show when "output" is "Prediction-Accuracy Table".
long.running.calculations	Allow categorical predictors with over 30 levels.
seed	The random number seed.
...	Other arguments to be supplied to rpart. Normally used for mincut, minsize or mindev

Details

Creates an rpart.object tree and plots it as a SankeyTree

Displayr/flipTrees documentation built on Feb. 26, 2024, 12:46 a.m.