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
num_terms: The number of features that will be retained in the
prod_degree: The highest possible degree of interaction between
features. A value of 1 indicates and 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
These arguments are converted to their specific names at the
time that the model is fit. Other options and argument can be
set_engine(). If left to their defaults
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.
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A single character string for the type of model. Possible values for this model are "unknown", "regression", or "classification".
The number of features that will be retained in the final model, including the intercept.
The highest possible interaction degree.
The pruning method.
A MARS model specification.
A 1-row tibble or named list with main
parameters to update. If the individual arguments are used,
these will supersede the values in
A logical for whether the arguments should be modified in-place of or replaced wholesale.
Not used for
The model can be created using the
fit() function using the
"earth" (the default)
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.
mars() %>% set_engine("earth") %>% set_mode("regression") %>% translate()
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## 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()
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## 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
fit() passes the data directly to
earth::earth() so that its
formula method can create dummy variables as-needed.
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.
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