Description Usage Arguments Value
Automatically models poisson targets with random search hyperparameter optimziation. XGBoost model trains with lossguide and histogram tree method to accelerate tuning.
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df_train |
Training data.frame with column called "target" for training. All columns should be numeric and prepared with a package like vtreat. |
df_test |
Testing data.frame with column called "target" for evaluation. All columns should be numeric and prepared with a package like vtreat. |
tune_rounds |
Integer (e.g. 25L) indicating the number of hyperoptimization tuning rounds. |
verbose |
Print model iterations (T/F). |
max_rounds |
Maximum number of rounds to use in model fitting. |
cv_folds |
Integer (e.g. 5L) that sets the number of cross validation folds to use in model tuning. |
early_stopping_rounds |
Integer (e.g. 10L) that sets xgb.cv early_stopping_rounds parameter. |
folds |
Allows users to specify their own folds (e.g. stratified folds). |
model, data, and model results
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