View source: R/grid-biregular.R
grid_biregular | R Documentation |
Biregular grids can be created for any number of parameter objects.
grid_biregular(
x,
...,
center = NULL,
levels = 3,
original = TRUE,
filter = NULL
)
x |
A |
... |
One or more |
center |
A numeric vector specifying the point onto which the biregular
grid should be centered. Defaults to |
levels |
An integer for the number of values of each parameter to use
to make the regular grid. |
original |
A logical: should the parameters be in the original units or in the transformed space (if any)? |
filter |
A logical: should the parameters be filtered prior to generating the grid. Must be a single expression referencing parameter names that evaluates to a logical vector. |
Note that there may a difference in grids depending on how the function
is called. If the call uses the parameter objects directly the possible
ranges come from the objects in dials
. For example:
mixture()
## Proportion of Lasso Penalty (quantitative) ## Range: [0, 1]
set.seed(283) mix_grid_1 <- grid_random(mixture(), size = 1000) range(mix_grid_1$mixture)
## [1] 0.001490161 0.999741096
However, in some cases, the parsnip
and recipe
packages overrides
the default ranges for specific models and preprocessing steps. If the
grid function uses a parameters
object created from a model or recipe,
the ranges may have different defaults (specific to those models). Using
the example above, the mixture
argument above is different for
glmnet
models:
library(parsnip) library(tune) # When used with glmnet, the range is [0.05, 1.00] glmn_mod <- linear_reg(mixture = tune()) %>% set_engine("glmnet") set.seed(283) mix_grid_2 <- grid_random(extract_parameter_set_dials(glmn_mod), size = 1000) range(mix_grid_2$mixture)
## [1] 0.05141565 0.99975404
A tibble. There are columns for each parameter and a row for every parameter combination.
grid_biregular(dials::mixture(), center = 0.2)
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