tune (version 0.1.2)

parameters.workflow: Determination of parameter sets for other objects

Description

These methods extend the generic dials::parameters() to work with more complex objects, such as recipes, model specifications, and workflows.

Usage

# S3 method for workflow
parameters(x, ...)
# S3 method for model_spec
parameters(x, ...)
# S3 method for recipe
parameters(x, ...)

Arguments

x

An object

...

Not currently used.

Value

A parameter set object

Examples

# NOT RUN {
library(tibble)
library(recipes)

recipe(mpg ~ ., data = mtcars) %>%
  step_knnimpute(all_predictors(), neighbors = tune()) %>%
  step_pca(all_predictors(), num_comp = tune()) %>%
  dials::parameters()

 # A peak under the hood
 tibble::as_tibble(.Last.value)

recipe(mpg ~ ., data = mtcars) %>%
  step_ns(disp, deg_free = tune("disp df")) %>%
  step_ns(wt, deg_free = tune("wt df")) %>%
  dials::parameters()

recipe(mpg ~ ., data = mtcars) %>%
  step_normalize(all_predictors()) %>%
  dials::parameters()

library(parsnip)

boost_tree(trees = tune(), min_n = tune()) %>%
  set_engine("xgboost") %>%
  dials::parameters()

boost_tree(trees = tune(), min_n = tune()) %>%
  set_engine("C5.0", rules = TRUE) %>%
  dials::parameters()
# }