expand_modelgrid {MachineShop}

Model Tuning Grid Expansion

Description

Expand a model grid of tuning parameter values.

Usage

expand_modelgrid(...)

## S3 method for class 'formula'
expand_modelgrid(formula, data, model, info = FALSE, ...)

## S3 method for class 'matrix'
expand_modelgrid(x, y, model, info = FALSE, ...)

## S3 method for class 'ModelFrame'
expand_modelgrid(input, model, info = FALSE, ...)

## S3 method for class 'recipe'
expand_modelgrid(input, model, info = FALSE, ...)

## S3 method for class 'ModelSpecification'
expand_modelgrid(object, ...)

## S3 method for class 'MLModel'
expand_modelgrid(model, ...)

## S3 method for class 'MLModelFunction'
expand_modelgrid(model, ...)

Arguments

...

arguments passed from the generic function to its methods and from the MLModel and MLModelFunction methods to others. The first argument of each expand_modelgrid method is positional and, as such, must be given first in calls to them.

formula, data

formula defining the model predictor and response variables and a data frame containing them.

model

model function, function name, or object; or another object that can be coerced to a model. A model can be given first followed by any of the variable specifications.

info

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

x, y

matrix and object containing predictor and response variables.

input

input object defining and containing the model predictor and response variables.

object

model specification.

Details

The expand_modelgrid function enables manual extraction and viewing of grids created automatically when a TunedModel is fit.

Value

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

See Also

TunedModel

Examples

expand_modelgrid(TunedModel(GBMModel, grid = 5))

expand_modelgrid(TunedModel(GLMNetModel, grid = c(alpha = 5, lambda = 10)),
                 sale_amount ~ ., data = ICHomes)

gbm_grid <- ParameterGrid(
  n.trees = dials::trees(),
  interaction.depth = dials::tree_depth(),
  size = 5
)
expand_modelgrid(TunedModel(GBMModel, grid = gbm_grid))

rf_grid <- ParameterGrid(
  mtry = dials::mtry(),
  nodesize = dials::max_nodes(),
  size = c(3, 5)
)
expand_modelgrid(TunedModel(RandomForestModel, grid = rf_grid),
                 sale_amount ~ ., data = ICHomes)