- default_regression_model
A model_spec object from library(parsnip)
for use in regression models.
- default_classification_model
A model_spec object from library(parsnip)
for use in classification models.
- custom_models
A list of named lists each with two elements:
vars for variable names, and model for their associated model.
from library(parsnip).
- default_regression_steps
A list of recipe::step_ function(s)
from library(recipes) for use in regression models.
- default_classification_steps
A list of recipe::step_ function(s)
from library(recipes) for use in classification models.
- custom_steps
A list of named lists each with two elements:
vars for variable names, and steps for their associated recipe.
- default_regression_sampler
A sampling function for drawing
new values from regression models.
- default_classification_sampler
A sampling function for drawing
new values from classification models.
- custom_samplers
A list of named lists each with two elements:
vars for variable names, and sampler for their associated sampler
- default_regression_noise
A noise function for adding noise to numeric
values.
- default_classification_noise
A noise function for adding noise to
classification values.
- custom_noise
A list of named lists each with two elements:
vars for variable names, and noise for their associated noise
- default_regression_tuner
A tuner from library(tune)
for use in regression models.
- default_classification_tuner
A tuner from library(tune)
for use in classification models.
- custom_tuners
A list of named lists each with two elements:
vars for variable names, and tuner for their associated tuner
- default_extractor
An optional method for extracting workflows or
extracts from workflows.
- custom_extractors
A list of named lists each with two elements:
vars for variable names, and extractor for their associated extractor
- invert_transformations
A Boolean for if outcome variable
transformations applied through recipes should be inverted during synthesis.
recipes need ids that begin with "outcome".
- enforce_na
A Boolean for if NA values should be added into the
synthetic data with enforce_na() during synthesis. An alternative approach
is to add the NA values after synthesis