setup_CART: Setup CART Hyperparameters

In egenn/rtemis: Machine Learning and Visualization

Setup CART Hyperparameters

Description

Setup hyperparameters for CART training.

Usage

setup_CART(
  cp = 0.01,
  maxdepth = 20L,
  minsplit = 2L,
  minbucket = 1L,
  prune_cp = NULL,
  method = "auto",
  model = TRUE,
  maxcompete = 4L,
  maxsurrogate = 5L,
  usesurrogate = 2L,
  surrogatestyle = 0L,
  xval = 0L,
  cost = NULL,
  ifw = FALSE
)

Arguments

cp	(Tunable) Numeric: Complexity parameter.
maxdepth	(Tunable) Integer: Maximum depth of tree.
minsplit	(Tunable) Integer: Minimum number of observations in a node to split.
minbucket	(Tunable) Integer: Minimum number of observations in a terminal node.
prune_cp	(Tunable) Numeric: Complexity for cost-complexity pruning after tree is built
method	String: Splitting method.
model	Logical: If TRUE, return a model.
maxcompete	Integer: Maximum number of competitive splits.
maxsurrogate	Integer: Maximum number of surrogate splits.
usesurrogate	Integer: Number of surrogate splits to use.
surrogatestyle	Integer: Type of surrogate splits.
xval	Integer: Number of cross-validation folds.
cost	Numeric (>=0): One for each feature.
ifw	Logical: If TRUE, use Inverse Frequency Weighting in classification.

Details

Get more information from rpart::rpart and rpart::rpart.control.

Value

CARTHyperparameters object.

Author(s)

EDG

egenn/rtemis documentation built on June 14, 2025, 11:54 p.m.