dropout: Neural network parameters

In dials: Tools for Creating Tuning Parameter Values

Neural network parameters

Description

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

Usage

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

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

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

hidden_units_2(range = c(1L, 10L), trans = NULL)

batch_size(range = c(unknown(), unknown()), trans = transform_log2())

Arguments

range	A two-element vector holding the defaults for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the transformed units.
trans	A trans object from the scales package, such as scales::transform_log10() or scales::transform_reciprocal(). 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()

dials documentation built on Sept. 11, 2024, 8:25 p.m.