These functions generate parameters that are useful for neural network models.

dropout(range = c(0, 1), trans = NULL)

epochs(range = c(10L, 1000L), trans = NULL)

hidden_units(range = c(1L, 10L), trans = NULL)

batch_size(range = c(unknown(), unknown()), trans = log2_trans())

## Arguments

range A two-element vector holding the defaults for the smallest and largest possible values, respectively. A trans object from the scales package, such as scales::log10_trans() or scales::reciprocal_trans(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

## Details

• dropout(): The parameter dropout rate. (See parsnip:::mlp()).

• epochs(): The number of iterations of training. (See parsnip:::mlp()).

• hidden_units(): The number of hidden units in a network layer. (See parsnip:::mlp()).

• batch_size(): The mini-batch size for neural networks.

## Examples

dropout()
#> Dropout Rate (quantitative)
#> Range: [0, 1)