parsnip: mars – R documentation

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mars

General Interface for MARS

Description

mars() is a way to generate a specification of a model before fitting and allows the model to be created using R. The main arguments for the model are:

num_terms: The number of features that will be retained in the final model.
prod_degree: The highest possible degree of interaction between features. A value of 1 indicates an additive model while a value of 2 allows, but does not guarantee, two-way interactions between features.
prune_method: The type of pruning. Possible values are listed in ?earth.

These arguments are converted to their specific names at the time that the model is fit. Other options and arguments can be set using set_engine(). If left to their defaults here (NULL), the values are taken from the underlying model functions. If parameters need to be modified, update() can be used in lieu of recreating the object from scratch.

Usage

mars(
  mode = "unknown",
  num_terms = NULL,
  prod_degree = NULL,
  prune_method = NULL
)

## S3 method for class 'mars'
update(
  object,
  parameters = NULL,
  num_terms = NULL,
  prod_degree = NULL,
  prune_method = NULL,
  fresh = FALSE,
  ...
)

Arguments

`mode`	A single character string for the type of model. Possible values for this model are "unknown", "regression", or "classification".
`num_terms`	The number of features that will be retained in the final model, including the intercept.
`prod_degree`	The highest possible interaction degree.
`prune_method`	The pruning method.
`object`	A MARS model specification.
`parameters`	A 1-row tibble or named list with main parameters to update. If the individual arguments are used, these will supersede the values in `parameters`. Also, using engine arguments in this object will result in an error.
`fresh`	A logical for whether the arguments should be modified in-place of or replaced wholesale.
`...`	Not used for `update()`.

Details

The model can be created using the fit() function using the following engines:

R: "earth" (the default)

Engine Details

Engines may have pre-set default arguments when executing the model fit call. For this type of model, the template of the fit calls are below.

earth

mars() %>% 
  set_engine("earth") %>% 
  set_mode("regression") %>% 
  translate()

## MARS Model Specification (regression)
## 
## Computational engine: earth 
## 
## Model fit template:
## earth::earth(formula = missing_arg(), data = missing_arg(), weights = missing_arg(), 
##     keepxy = TRUE)

mars() %>% 
  set_engine("earth") %>% 
  set_mode("classification") %>% 
  translate()

## MARS Model Specification (classification)
## 
## Engine-Specific Arguments:
##   glm = list(family = stats::binomial)
## 
## Computational engine: earth 
## 
## Model fit template:
## earth::earth(formula = missing_arg(), data = missing_arg(), weights = missing_arg(), 
##     glm = list(family = stats::binomial), keepxy = TRUE)

Note that, when the model is fit, the earth package only has its namespace loaded. However, if multi_predict is used, the package is attached.

Also, fit() passes the data directly to earth::earth() so that its formula method can create dummy variables as-needed.

For this engine, tuning over num_terms is very efficient since the same model object can be used to make predictions over multiple values of num_terms.

Parameter translations

The standardized parameter names in parsnip can be mapped to their original names in each engine that has main parameters. Each engine typically has a different default value (shown in parentheses) for each parameter.

parsnip	earth
num_terms	nprune
prod_degree	degree (1)
prune_method	pmethod (backward)

Examples

show_engines("mars")

mars(mode = "regression", num_terms = 5)
model <- mars(num_terms = 10, prune_method = "none")
model
update(model, num_terms = 1)
update(model, num_terms = 1, fresh = TRUE)

parsnip

A Common API to Modeling and Analysis Functions

v0.1.5

GPL-2

Authors

Max Kuhn [aut, cre], Davis Vaughan [aut], RStudio [cph]

Initial release