MachineShop (version 2.7.0)

get_grid: Model Tuning Grid

Description

Extract a model-defined grid of tuning parameter values.

Usage

get_grid(x, ...)
# S3 method for default
get_grid(x, ..., model, size = 3, random = FALSE, info = FALSE)
# S3 method for formula
get_grid(x, data, ...)
# S3 method for matrix
get_grid(x, y, ...)
# S3 method for ModelFrame
get_grid(x, ...)
# S3 method for recipe
get_grid(x, ...)
# S3 method for MLModel
get_grid(x, ...)
# S3 method for MLModelFunction
get_grid(x, ...)

Arguments

x

optional input specifying a relationship between model predictor and response variables. Alternatively, a model function or call may be given first followed by the input specification.

...

arguments passed to the default method.

model

model function, function name, or call.

size

single integer or vector of integers whose positions or names match the parameters in the model's tuning grid and which specify the number of values to use in constructing the grid.

random

number of unique grid points to sample at random, Inf for all random points, or FALSE for all fixed points.

info

logical indicating whether to return the grid construction information rather than the grid values.

data

data frame containing observed predictors and outcomes.

y

response variable.

Value

A data frame of parameter values or NULL if data are required for construction of the grid but not supplied.

Details

The get_grid function enables manual extraction and viewing of grids created automatically if TunedModel is called with a Grid object.

See Also

TunedModel, Grid

Examples

# NOT RUN {
get_grid(GBMModel, size = 10)

get_grid(sale_amount ~ ., data = ICHomes, model = GLMNetModel,
         size = c(lambda = 10, alpha = 5))

# }