Bayesian optimization with cross validation
Usage
bayesOptCV(
rec = NULL,
model = NULL,
v = NULL,
trainingData = NULL,
gridNum = NULL,
iter = NULL,
seed = NULL
)Arguments
- rec
The recipe object including local preprocessing.
- model
The model object including the list of hyperparameters, engine and mode.
- v
Perform cross-validation by dividing the training data into v folds.
- trainingData
The training data.
- gridNum
Initial number of iterations to run before starting the optimization algorithm.
- iter
The maximum number of search iterations.
- seed
Seed for reproducible results.