crumble_control {crumble} | R Documentation |
Crumble control parameters
Description
Crumble control parameters
Usage
crumble_control(
crossfit_folds = 10L,
mlr3superlearner_folds = 10L,
zprime_folds = 1L,
epochs = 100L,
learning_rate = 0.01,
batch_size = 64,
device = c("cpu", "cuda", "mps")
)
Arguments
crossfit_folds |
[numeric(1) ] The number of crossfit folds.
|
mlr3superlearner_folds |
[numeric(1) ] The number of 'mlr3superlearner' folds.
|
zprime_folds |
[numeric(1) ] The number of folds to split that data into for calculating Z'.
With larger sample sizes, a larger number will increase speed.
|
epochs |
[numeric(1) ] The number of epochs to train the neural network.
|
learning_rate |
[numeric(1) ] The learning rate for the neural network.
|
batch_size |
[numeric(1) ] The batch size for mini-batch gradient descent.
|
device |
[character(1) ] Object representing the device on which a torch_tensor is or will be allocated.
|
Value
A list of control parameters
Examples
if (torch::torch_is_installed()) crumble_control(crossfit_folds = 5)
[Package
crumble version 0.1.2
Index]