tune_xgboost: Train and test XGBoost classifier.

In anpatton/overdoseR: Predictive Modeling for Opioid Overdoses from EMS Data

Description

Train and test XGBoost classifier.

Usage

tune_xgboost(
  training_data,
  testing_data,
  save_model = TRUE,
  model_name = paste0("opioid_xgboost_model_", Sys.Date()),
  target = "opioid",
  features = "defaults",
  cv_iters = 5,
  tune_iters = 50
)

Arguments

training_data	formatted EMS data for model training
testing_data	formatted EMS data for model training
save_model	Logical flag to save model as .RDS object
model_name	Filepath and name of model to save, .RDS extension not needed
target	Binary (0/1) for class labels
features	Character vector of features, "default" for recommended options
cv_iters	Number of cross validation folds for use in tuning - must be greater than 1
tune_iters	Number of overall tuning iterations - must be greater than 1

Value

List object with model and test data with predictions

• model - Fitted XGBoost object

• tune_obj - XGBoost tuning object

• results - Test data with predictions

Examples

## Not run: tune_xgboost(training_data = train, testing_data = test)

anpatton/overdoseR documentation built on July 16, 2020, 1:53 a.m.