decision_tree_exposure: Poisson Decision Trees with Exposures

In offsetreg: An Extension of 'Tidymodels' Supporting Offset Terms

Poisson Decision Trees with Exposures

Description

decision_tree_exposure() defines a Poisson decision tree model with weighted exposures (observation times).

Usage

decision_tree_exposure(
  mode = "regression",
  engine = "rpart_exposure",
  cost_complexity = NULL,
  tree_depth = NULL,
  min_n = NULL
)

Arguments

mode	A single character string for the type of model. The only possible value for this model is "regression"
engine	A single character string specifying what computational engine to use for fitting.
cost_complexity	A positive number for the the cost/complexity parameter (a.k.a. Cp) used by CART models (specific engines only).
tree_depth	An integer for maximum depth of the tree.
min_n	An integer for the minimum number of data points in a node that are required for the node to be split further.

Details

This function is similar to parsnip::decision_tree() except that specification of an exposure column is required.

Value

A model specification object with the classes decision_tree_exposure and model_spec.

See Also

parsnip::decision_tree()

Examples

parsnip::show_model_info("decision_tree_exposure")

decision_tree_exposure()

offsetreg documentation built on April 4, 2025, 1:35 a.m.