tl_tune_xgboost: Tune XGBoost hyperparameters

In tidylearn: A Unified Tidy Interface to R's Machine Learning Ecosystem

Tune XGBoost hyperparameters

Description

Tune XGBoost hyperparameters

Usage

tl_tune_xgboost(
  data,
  formula,
  is_classification = FALSE,
  param_grid = NULL,
  cv_folds = 5,
  early_stopping_rounds = 10,
  verbose = TRUE,
  ...
)

Arguments

data	A data frame containing the training data
formula	A formula specifying the model
is_classification	Logical indicating if this is a classification problem
param_grid	Named list of parameter values to try
cv_folds	Number of cross-validation folds (default: 5)
early_stopping_rounds	Early stopping rounds (default: 10)
verbose	Logical indicating whether to print progress (default: TRUE)
...	Additional arguments

Value

A list with the best model and tuning results

tidylearn documentation built on Feb. 6, 2026, 5:07 p.m.