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MachineShop (version 3.8.0)

expand_modelgrid: Model Tuning Grid Expansion

Description

Expand a model grid of tuning parameter values.

Usage

expand_modelgrid(...)

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

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

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

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

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

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

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

Value

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

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.

See Also

TunedModel

Examples

Run this code
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)

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