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Rpart wrapper for causal distillation trees.

student_rpart.Rd

This function is a wrapper around rpart::rpart() that can be easily used as a student model in the causal distillation tree framework.

Usage

student_rpart(
  X,
  y,
  method = "anova",
  rpart_control = NULL,
  prune = c("none", "min", "1se"),
  fit_only = FALSE
)

Arguments

X

A tibble, data.frame, or matrix of covariates.

y

A vector of responses to predict.

method

Same as method argument in rpart::rpart(). Default is "anova". See rpart::rpart() for more details.

rpart_control

A list of control parameters for the rpart algorithm. See ? rpart.control for details.

prune

Method for pruning the tree. Default is "none". Options are "none", "min", and "1se". If "min", the tree is pruned using the complexity threshold which minimizes the cross-validation error. If "1se", the tree is pruned using the largest complexity threshold which yields a cross-vaidation error within one standard error of the minimum. If "none", the tree is not pruned.

fit_only

Logical. If TRUE, only the fitted model is returned. Default is FALSE.

Value

If fit_only = TRUE, the fitted model is returned. Otherwise, a list with the following components is returned:

fit

Fitted model. An rpart model object.

tree_info

Data frame with tree structure/split information.

subgroups

List of subgroups given by their string representation.

predictions

Student model predictions for the given X data.