fast_regression: Generate Model Specification calls to 'parsnip'

In tidyAML: Automatic Machine Learning with 'tidymodels'

Generate Model Specification calls to parsnip

Description

Creates a list/tibble of parsnip model specifications.

Usage

fast_regression(
  .data,
  .rec_obj,
  .parsnip_fns = "all",
  .parsnip_eng = "all",
  .split_type = "initial_split",
  .split_args = NULL,
  .drop_na = TRUE
)

Arguments

.data	The data being passed to the function for the regression problem
.rec_obj	The recipe object being passed.
.parsnip_fns	The default is 'all' which will create all possible regression model specifications supported.
.parsnip_eng	the default is 'all' which will create all possible regression model specifications supported.
.split_type	The default is 'initial_split', you can pass any type of split supported by rsample
.split_args	The default is NULL, when NULL then the default parameters of the split type will be executed for the rsample split type.
.drop_na	The default is TRUE, which will drop all NA's from the data.

Details

With this function you can generate a tibble output of any regression model specification and it's fitted workflow object.

Value

A list or a tibble.

Author(s)

Steven P. Sanderson II, MPH

See Also

Other Model_Generator: create_model_spec(), fast_classification()

Examples

library(recipes, quietly = TRUE)

rec_obj <- recipe(mpg ~ ., data = mtcars)
frt_tbl <- fast_regression(
  mtcars,
  rec_obj,
  .parsnip_eng = c("lm","glm","gee"),
  .parsnip_fns = "linear_reg"
  )

frt_tbl

tidyAML documentation built on May 29, 2024, 4:07 a.m.