bestEATBoost {boostingDEA} | R Documentation |
This function computes the root mean squared error (RMSE) for a set of EATBoost models built with a grid of given hyperparameters.
bestEATBoost(
training,
test,
x,
y,
num.iterations,
learning.rate,
num.leaves,
verbose = TRUE
)
training |
Training |
test |
Test |
x |
Column input indexes in |
y |
Column output indexes in |
num.iterations |
Maximum number of iterations the algorithm will perform |
learning.rate |
Learning rate that control overfitting of the algorithm. Value must be in (0,1] |
num.leaves |
Maximum number of terminal leaves in each tree at each iteration |
verbose |
Controls the verbosity. |
A data.frame
with the sets of hyperparameters and the root
mean squared error (RMSE) and mean square error (MSE) associated for each
model.